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Pipeline run

d3644468-a2ee-4dd3-87dd-d2472ce29bc8

Pipeline LLM cost (USD)
API 1: $0.0115 API 2: $0.0005 API 3: $0.0000 Total: $0.0120

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
role baseline loaded sources · ai_index: jd · nature_of_work: jd · tech_stack_maturity: jd
Nature of work · Data pipeline development
Build and optimize Azure data/analytics pipelines in ADF, Synapse, Databricks and PySpark, including batch/streaming ingestion, lakehouse modeling, and governance/security controls. Also develop Azure OpenAI/RAG apps and Python APIs hosted on Azure services.
"Design and implement scalable data ingestion and transformation pipelines using Azure Data Factory, Azure Synapse Pipelines, Databricks, and serverless compute"
Tech stack maturity
Modern Cloud Native
The stack is centered on Azure cloud services, Kubernetes, CI/CD, and modern data/ML platforms like Databricks, Synapse, Delta Lake, and Azure OpenAI, which aligns with a modern cloud-native environment.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
1.70 / 5
· Title match
Has AI skill
AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1): Copilot
Frameworks (×2): LangChain, LlamaIndex, Hugging Face, Bedrock, Vertex AI, Azure OpenAI
Models / concepts (×3): OpenAI, Transformers, RAG, fine-tuning, LoRA, LLMOps, MLOps, prompt engineering, AI, GenAI, Machine Learning, Artificial Intelligence
Evidence — skills matched in JD (54)
Azure Data Factory Azure Synapse Analytics Azure Synapse Pipelines Azure Databricks Databricks ADLS Gen2 Azure Storage PySpark Python SQL Azure Event Hubs Azure Stream Analytics Kafka Delta Lake Lakehouse Architecture Azure AD Managed Identities RBAC Azure Key Vault Docker Git CI/CD Azure DevOps GitHub Azure Purview +29
Skill cluster (18 dimension groups, role-scoped)
Cloud Platforms
Azure OpenAI Azure App Service AWS Bedrock
Web Application Frameworks
FastAPI Flask Django
Programming Languages for Data Work
Python SQL
Angular Component Model and Templates
Angular
Authentication and Authorization
RBAC
BI and Visualization Tools
Power BI
Cloud Data Warehouses
Azure Synapse Analytics
Cloud Platforms & Managed Services
Azure Functions
Containerization and Image Builds
Docker
Data Lineage and Metadata
MLOps
Identity and Access Management Products
Azure AD
Infrastructure as Code
Terraform
Integration Protocols & Standards
REST
LLM Serving & Deployment
LLMOps
Messaging and Event Streaming
Kafka
React Component Architecture
React
Secrets and Identity Automation
Azure Key Vault
Cross-cutting / unaligned
Azure Data Factory Azure Synapse Pipelines Azure Databricks Databricks ADLS Gen2 Azure Storage PySpark Azure Event Hubs Azure Stream Analytics Delta Lake Lakehouse Architecture Managed Identities Git CI/CD Azure DevOps GitHub Azure Purview Azure OpenAI Service Azure AI services Azure Cognitive Search Azure AI Search AKS Azure Machine Learning Bicep Hugging Face Transformers PEFT LoRA LangChain LlamaIndex SharePoint Microsoft 365 Vertex AI
Show KRA description ↓
Design and implement scalable data ingestion and transformation pipelines using Azure Data Factory, Azure Synapse Pipelines, Databricks, and serverless compute; build and manage data lakes and lakehouse architectures using ADLS, Delta Lake, and enterprise Azure warehouse components; develop PySpark/Python data processing jobs for batch and streaming; implement real-time ingestion with Azure Event Hubs, Azure Stream Analytics, or Kafka; apply best practices for data modeling, partitioning, indexing, compression, cost optimization, and performance tuning across Azure platforms; ensure data quality, lineage, metadata management, and auditing across the lifecycle; implement security and governance with Azure AD, Managed Identities, Key Vault, network isolation, and fine-grained RBAC; design and develop GenAI applications using Azure OpenAI and Azure AI services; implement RAG architectures using Azure Cognitive Search / Azure AI Search and Azure data stores; integrate GenAI solutions with ADLS, Synapse, SQL, SharePoint, and Microsoft 365; build Python APIs, microservices, and backends with FastAPI/Flask hosted on Azure Functions, App Service, or AKS; implement prompt. Azure Data Factory, Azure Synapse Analytics, Azure Databricks, ADLS Gen2, Azure Storage, PySpark, Python, SQL, Data Warehousing, ETL/ELT, Data Modeling, Azure SQL / SQL MI, Azure OpenAI Service, Azure Cognitive Services, Azure Cognitive Search / Azure AI Search, LangChain, LlamaIndex, REST API Development (FastAPI/Flask/Django), Azure Functions, Azure App Service, Azure AD, Managed Identities, RBAC, Azure Key Vault, Encryption, Docker, Git, CI/CD (Azure DevOps/GitHub). Azure Event Hubs, Kafka, Azure Stream Analytics, Delta Lake / Lakehouse Architecture, Azure Purview, Power BI Integration, Azure Machine Learning, Azure OpenAI Integration, Terraform / Bicep, Cost Optimization on Azure Data Services, Real-time Analytics, Hugging Face Transformers, PEFT / LoRA Fine-tuning, Multi-cloud GenAI Platforms (Azure OpenAI / AWS Bedrock / Vertex AI), Prompt Engineering Techniques, Frontend Integration (React / Angular) for chatbots, LLMOps / MLOps, Monitoring & Logging for GenAI, Security & Compliance for AI workloads.

Signals

Skill backend-engineer
0.25
Alias
KRA data-engineer
0.57

Post-classification

Centroidupdated · n=493
Alias collision log
New-role queue
New skills captured18
New KRA captured

Captured for admin review

Azure Data Factory primary Data Engineer pending
Azure Synapse Pipelines primary Data Engineer pending
Azure Databricks primary Data Engineer pending
ADLS Gen2 primary Data Engineer pending
Azure Storage primary Data Engineer pending
PySpark primary Data Engineer pending
Azure Event Hubs primary Data Engineer pending
Azure Stream Analytics primary Data Engineer pending
Lakehouse Architecture primary Data Engineer pending
Managed Identities primary Data Engineer pending
Azure Purview primary Data Engineer pending
Azure Machine Learning Data Engineer pending
Hugging Face Transformers Data Engineer pending
Azure OpenAI Service primary Data Engineer pending
Azure AI services primary Data Engineer pending
Azure AI Search primary Data Engineer pending
SharePoint Data Engineer pending
Microsoft 365 Data Engineer pending
Status: completed Created: 2026-05-27T17:17:15.882497Z Updated: 2026-06-07T20:19:13.715373Z API 3 duration: 31733 ms
Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

Data Engineer

domain · Data Engineering & Analytics CASE DOMAIN

slug: data-engineer · id: 2 · source: db

Domain=Data Engineering & Analytics; The JD is primarily for a cloud data engineer building Azure-based ingestion, transformation, lakehouse, streaming, and pipeline solutions, with additional GenAI and API work.

Matched skills

Azure Data FactoryAzure Synapse PipelinesDatabricksADLSDelta LakePySparkPythonAzure Event HubsAzure Stream AnalyticsKafkaAzure OpenAIAzure Cognitive SearchFastAPIFlaskAzure Functions

Matched dimensions

Data Pipeline EngineeringLakehouse ArchitectureBatch and Streaming Data ProcessingReal-time Data IngestionData Modeling and Performance TuningData Quality and GovernanceAzure Security and Access ControlGenAI Application Development

Matched KRAs

Design and implement scalable data ingestion and transformation pipelinesBuild and manage data lakes and lakehouse architecturesDevelop PySpark/Python data processing jobs for batch and streamingImplement real-time ingestion with Azure Event HubsApply best practices for data modeling, partitioning, indexing, compressionEnsure data quality, lineage, metadata management, and auditingImplement security and governance with Azure AD, Managed IdentitiesDesign and develop GenAI applications using Azure OpenAI

Resolution: in_db — role exists in library; skill↔dim and role↔dim links saved when applicable.

0
New skills
0
Skill↔dim saved
0
Role↔dim saved
9
Skipped

Job description

Line of Service
Advisory


Industry/Sector
Not Applicable


Specialism
Emerging Technologies


Management Level
Senior Associate


Job Description & Summary
At PwC, our people in software and product innovation focus on developing cutting-edge software solutions and driving product innovation to meet the evolving needs of clients. These individuals combine technical experience with creative thinking to deliver innovative software products and solutions.

In emerging technology at PwC, you will focus on exploring and implementing cutting-edge technologies to drive innovation and transformation for clients. You will work in areas such as artificial intelligence, blockchain, and the internet of things (IoT).

*Why PWCAt PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us.At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. "
Job Description & Summary: A career in our New Technologies practice, within Application and Emerging Technology services, offers the opportunity to design and build modern, cloud-native solutions on Microsoft Azure that power the next generation of digital businesses. You will help clients create scalable, secure, and high-performing data and AI platforms by leveraging Azure services such as Azure Synapse, Azure Databricks, Azure Data Factory, Azure OpenAI Service, and Azure Cognitive Services. Our team focuses on building end-to-end data pipelines, lakehouse architectures, and enterprise-grade GenAI solutions—including intelligent applications, copilots, and domain-specific assistants—that enable advanced analytics, automation, and innovation. We emphasize secure, compliant, and scalable architectures that help organizations unlock the value of their data and transform how they operate and compete.

Responsibilities:

Design and implement scalable data ingestion and transformation pipelines using Azure Data Factory, Azure Synapse Pipelines, Databricks, and serverless compute; build and manage data lakes and lakehouse architectures using ADLS, Delta Lake, and enterprise Azure warehouse components; develop PySpark/Python data processing jobs for batch and streaming; implement real-time ingestion with Azure Event Hubs, Azure Stream Analytics, or Kafka; apply best practices for data modeling, partitioning, indexing, compression, cost optimization, and performance tuning across Azure platforms; ensure data quality, lineage, metadata management, and auditing across the lifecycle; implement security and governance with Azure AD, Managed

Identities, Key Vault, network isolation, and fine-grained RBAC; design and develop GenAI applications using Azure OpenAI and Azure AI services; implement RAG architectures using Azure Cognitive Search / Azure AI Search and Azure data stores; integrate GenAI solutions with ADLS, Synapse, SQL, SharePoint, and Microsoft 365; build Python APIs, microservices, and backends with FastAPI/Flask hosted on Azure Functions, App Service, or AKS; implement prompt

Mandatory skill sets:

Azure Data Factory, Azure Synapse Analytics, Azure Databricks, ADLS Gen2, Azure Storage, PySpark, Python, SQL, Data Warehousing, ETL/ELT, Data Modeling, Azure SQL / SQL MI, Azure OpenAI Service, Azure Cognitive Services, Azure Cognitive Search / Azure AI Search, LangChain, LlamaIndex, REST API Development (FastAPI/Flask/Django), Azure Functions, Azure App Service, Azure AD, Managed Identities, RBAC, Azure Key Vault, Encryption, Docker, Git, CI/CD (Azure DevOps/GitHub)

Preferred skill sets:

Azure Event Hubs, Kafka, Azure Stream Analytics, Delta Lake / Lakehouse Architecture, Azure Purview, Power BI Integration, Azure Machine Learning, Azure OpenAI Integration, Terraform / Bicep, Cost Optimization on Azure Data Services, Real-time Analytics, Hugging Face Transformers, PEFT / LoRA Fine-tuning, Multi-cloud GenAI Platforms (Azure OpenAI / AWS Bedrock / Vertex AI), Prompt Engineering Techniques, Frontend Integration (React / Angular) for chatbots, LLMOps / MLOps,

Monitoring & Logging for GenAI, Security & Compliance for AI workloads

Years of experience required:

4-7

Education qualification-Full

Time:

B.E/B.Tech/M.Tech/MBA/MCA




Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Master of Business Administration, Bachelor of Technology

Degrees/Field of Study preferred:


Certifications (if blank, certifications not specified)


Required Skills
Microsoft Azure


Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Analytical Thinking, Artificial Intelligence, Business Planning and Simulation (BW-BPS), Communication, Competitive Advantage, Conducting Research, Creativity, Digital Transformation, Embracing Change, Emotional Regulation, Empathy, Implementing Technology, Inclusion, Innovation Processes, Intellectual Curiosity, Internet of Things (IoT), Learning Agility, Optimism, Product Development, Product Testing, Prototyping, Quality Assurance Process Management {+ 10 more}


Desired Languages (If blank, desired languages not specified)


Travel Requirements


Available for Work Visa Sponsorship?


Government Clearance Required?


Job Posting End Date

Skills from this JD

Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.

Azure Data Factory Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
Data Integration
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure Synapse Analytics Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure Synapse Analytics id=108 · azure-synapse-analytics

Aliases — catalog

  • Azure Synapse Analytics (CANONICAL) primary

Context tags (catalog)

Apache Spark Azure Data Lake Storage Data Factory Delta Lake PolyBase SQL pools Spark pools Synapse Studio T-SQL dedicated SQL pool linked services notebooks pipelines serverless SQL pool workspace

Stored enrichment (catalog DB)

Category
Service
Sub-category
Analytics Service
Vendor
Microsoft
License
proprietary
Year introduced
2019
Confidence
0.95
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common in cloud data-platform JDs and Microsoft’s Azure analytics stack; often listed alongside Databricks/ADF for warehousing and ETL, indicating broad hiring demand.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
117
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Data Warehouses Catalog dimension db id 22

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Data Warehouses
cloud-data-warehouses
Existing dimension (library) · Role↔dimension saved
Azure Synapse Pipelines Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
Data Integration
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure Databricks Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
Data Engineering
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Databricks Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Databricks id=1202 · databricks

Aliases — catalog

  • Databricks (CANONICAL)

Context tags (catalog)

Apache Spark Databricks Runtime Delta Lake MLflow SQL Analytics Spark cloud integration collaborative workspace data engineering data lakes data pipelines data visualization job scheduling machine learning notebooks real-time analytics

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Data Analytics Platform
Vendor
Databricks, Inc.
License
other_open
Year introduced
2013
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: Databricks appears frequently in data engineering and analytics job postings, especially alongside Spark, Delta Lake, and lakehouse stacks; strong vendor adoption and broad enterprise usage signal mainstream demand.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
911
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
ADLS Gen2 Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
Storage
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure Storage Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure Blob Storage id=172 · azure-blob-storage

Aliases — catalog

  • Azure Blob Storage (CANONICAL) primary

Context tags (catalog)

AzCopy Azure Storage Explorer Azurite Managed Identity SAS token access tiers blob trigger blobs containers event grid hot/cool/archive immutable storage lifecycle management managed identity private endpoint replication shared access signature storage account

Stored enrichment (catalog DB)

Category
Service
Sub-category
Object Storage Service
Vendor
Microsoft
License
proprietary
Year introduced
2008
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Broadly used object storage on Azure; appears frequently in cloud/data engineering JDs and Microsoft positions it as a core storage service, with no sunset or replacement signal.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
120
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Storage and Data Services Catalog dimension db id 144

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

  • Cloud Storage and File Formats Catalog dimension db id 35

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Storage and Data Services
cloud-storage-and-data-services
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Cloud Storage and File Formats
cloud-storage-and-file-formats
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
PySpark Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Apache Spark id=1350 · apache-spark

Aliases — catalog

  • Apache Spark (CANONICAL)
  • apache spark 3 (VERSION)
  • spark (VERSION)
  • spark 3 (VERSION)
  • spark 3.x (VERSION)
  • spark3 (VERSION)

Context tags (catalog)

Apache Kafka Cluster Manager DAGScheduler Data Lake DataFrame ETL Hadoop MLlib Machine Learning PySpark RDD Scala Spark SQL Spark Streaming SparkSession

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Distributed Data Processing Framework
Vendor
Apache Software Foundation
License
apache_2
Year introduced
2010
Confidence
0.94
Version strategy
SEPARATE_ENTITY
Version tag
3.x

Maturity reasoning: Apache Spark appears in many data engineering JDs and remains a standard for distributed ETL/ELT; its GitHub and vendor ecosystem activity stay strong, with Databricks and cloud platforms still promoting it.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
1021
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • ETL and ELT Tooling Catalog dimension db id 24

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
ETL and ELT Tooling
etl-and-elt-tooling
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Python Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Python id=5 · python

Aliases — catalog

  • Python (CANONICAL) primary
  • Python 2 (VERSION)
  • Python 2.x (VERSION)
  • Python 3 (VERSION)
  • Python 3.10 (VERSION)
  • Python 3.11 (VERSION)
  • Python 3.12 (VERSION)
  • Python 3.x (VERSION)
  • py (VERSION)
  • py2 (VERSION)
  • py3 (VERSION)
  • python 3 (VERSION)
  • python 3.x (VERSION)
  • python2 (VERSION)
  • python3 (VERSION)
  • python3.x (VERSION)

Context tags (catalog)

API Django FastAPI Flask Jupyter NumPy PEP 8 Pandas REST SQLAlchemy asyncio pandas pip pytest type hints venv virtualenv

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
PSF
License
mit
Year introduced
1991
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
3

Maturity reasoning: Python appears in a very high volume of job descriptions across data, backend, automation, and ML roles, and remains a default hiring-pipeline language on major job boards and tech stacks.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
96
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Security Scripting & DSL Languages Catalog dimension db id 248

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer

  • Programming Languages & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • Programming Languages and Scripting Catalog dimension db id 59

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • Programming Languages for XR Catalog dimension db id 97

    Library dimension (catalog)

    Roles linked in library: AR/VR Engineer

  • Python Programming Catalog dimension db id 290

    Library dimension (catalog)

    Roles linked in library: Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: SQL id=101 · sql

Aliases — catalog

  • SQL (CANONICAL) primary

Context tags (catalog)

ACID CTE DDL DML ETL JOIN MySQL NoSQL OLAP ORM PostgreSQL SQL injection SQLite T-SQL data modeling data warehousing database normalization execution plan indexing joins normalization query optimization stored procedures subquery transaction isolation transaction management window functions

Stored enrichment (catalog DB)

Category
Language
Sub-category
Query Language
Vendor
ANSI
License
unknown
Year introduced
1974
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: SQL appears in a large share of data, backend, and analytics job descriptions and remains the default query language for PostgreSQL, MySQL, and cloud warehouses like Snowflake/BigQuery.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
97
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Pega Programming Languages & DSLs Catalog dimension db id 267

    Library dimension (catalog)

    Roles linked in library: Pega Developer

  • Programming Languages & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Azure Event Hubs Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
Messaging
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure Stream Analytics Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
Data Streaming
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Kafka Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Kafka id=36 · kafka

Aliases — catalog

  • Kafka (CANONICAL) primary

Context tags (catalog)

Apache Flink Apache Kafka Apache Pulsar Apache Spark Avro KSQL Kafka API Kafka Connect Kafka Streams ZooKeeper Zookeeper backpressure brokers consumer consumer group consumer groups event sourcing event-driven architecture exactly-once semantics fault tolerance high throughput log compaction message broker message queue microservices offsets partition partitioning partitions producer producer API real-time analytics real-time data replication schema registry stream processing topic topic partitioning topics

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Event Stream Store
Vendor
Confluent
License
apache_2
Year introduced
2011
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Kafka appears in many production JDs for event streaming and data pipelines, and remains a standard platform in cloud/vendor offerings (e.g., Confluent, AWS MSK), indicating broad hiring demand.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
3
Sub-category id
3533
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Asynchronous Messaging and Event Streaming Catalog dimension db id 297

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Go Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Scala Backend Developer

  • Messaging and Background Jobs Catalog dimension db id 291

    Library dimension (catalog)

    Roles linked in library: PHP Backend Developer, Python Backend Developer, Ruby Backend Developer

  • Messaging and Event Streaming Catalog dimension db id 8

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Messaging and Background Jobs
messaging-and-background-jobs
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Messaging and Event Streaming
messaging-and-event-streaming
Existing dimension (library) · Role↔dimension saved
Delta Lake Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Delta Lake id=237 · delta-lake

Aliases — catalog

  • Delta Lake (CANONICAL) primary

Context tags (catalog)

ACID transactions Apache Spark CDC Databricks Delta Engine ETL Lakehouse architecture MERGE INTO OPTIMIZE Parquet Unity Catalog Z-Order batch processing cloud storage data governance data lake data lakehouse data pipeline data reliability partition pruning schema enforcement schema evolution streaming data streaming ingestion time travel

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Table Format Tool
Vendor
Databricks
License
apache_2
Year introduced
2017
Confidence
0.72
Version strategy
NOT_APPLICABLE

Maturity reasoning: Delta Lake appears frequently in data engineering JDs and cloud vendor docs, especially alongside Databricks/Spark for lakehouse stacks; it’s a common hiring-pipeline skill rather than a niche tool.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
1170
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Model and Data Versioning Catalog dimension db id 48

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Model and Data Versioning
model-and-data-versioning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Lakehouse Architecture Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Lakehouse id=1359 · lakehouse

Aliases — catalog

  • Lakehouse (CANONICAL)

Context tags (catalog)

Apache Spark Delta Lake ETL SQL analytics cloud storage data governance data integration data lake data modeling data pipeline data warehouse metadata management real-time processing streaming analytics

Stored enrichment (catalog DB)

Category
Architecture
Sub-category
Data Platform Architecture
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Lakehouse is increasingly listed in data-platform JDs and vendor docs (Databricks, Snowflake, Microsoft Fabric), but it is not yet as universal as core warehouse or lake skills.

Skill profile (library / DB)

Skill nature
PATTERN
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
1
Sub-category id
1026
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Azure AD Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure AD id=342 · azure-ad

Aliases — catalog

  • Azure AD (CANONICAL) primary

Context tags (catalog)

App registrations Azure AD Connect Azure Active Directory B2B B2B Collaboration B2C Conditional Access Directory Synchronization Enterprise Applications Enterprise applications Entra ID Graph API Identity Governance Identity Protection MFA Multi-Factor Authentication OAuth OAuth 2.0 OpenID Connect RBAC SAML SCIM SSO service principals

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Vendor Saas Platform
Vendor
Microsoft
License
proprietary
Year introduced
2013
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: Azure AD (now Microsoft Entra ID) appears broadly in enterprise JDs for SSO, IAM, and Microsoft 365 integration; Microsoft’s rename shows evolution, not sunset, and demand remains high across cloud/security roles.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
784
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Identity and Access Architecture Catalog dimension db id 137

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, Cloud Security Engineer

  • Identity and Access Management Products Catalog dimension db id 65

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Identity and Access Architecture
identity-and-access-architecture
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Identity and Access Management Products
identity-and-access-management-products
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Managed Identities Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
Security
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
RBAC Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: RBAC id=29 · rbac

Aliases — catalog

  • RBAC (CANONICAL) primary

Context tags (catalog)

ACL IAM LDAP OAuth SAML access control access matrix access policies attribute-based access attribute-based access control audit trails authorization compliance entitlements group membership identity management least privilege multi-factor authentication multi-tenancy permissions policy policy enforcement principle of least privilege privilege escalation privileges resource access role hierarchy role-based access control roles security model security policies segregation of duties user management user roles

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Access Control Concept
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: RBAC is a standard access-control model widely listed in security and IAM job descriptions, and it underpins common products like AWS IAM and Kubernetes RBAC.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
5
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Authentication and Authorization Catalog dimension db id 6

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Go Backend Developer, Java Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer

  • Backend Authentication and Authorization Catalog dimension db id 386

    Library dimension (catalog)

    Roles linked in library: Kotlin Backend Developer, Ruby Backend Developer, Scala Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Authentication and Authorization
authentication-and-authorization
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Backend Authentication and Authorization
backend-authentication-and-authorization
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Key Vault Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure Key Vault id=873 · azure-key-vault

Aliases — catalog

  • Azure Key Vault (CANONICAL) primary

Context tags (catalog)

Azure Active Directory Azure CLI RBAC REST API SDK access policies audit logs certificate management certificates data protection data security encryption key protection key rotation key vault references managed identities secrets management vault access vaults

Stored enrichment (catalog DB)

Category
Service
Sub-category
Key Management Service
Vendor
Microsoft
License
proprietary
Year introduced
2016
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common in cloud/security JDs for secrets and key management; Microsoft positions it as a core Azure service and it appears alongside AKS/App Service/CI-CD in many enterprise postings.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
644
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cryptography and PKI Catalog dimension db id 67

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer, Cyber Security Engineer

  • Secrets and Identity Automation Catalog dimension db id 154

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cryptography and PKI
cryptography-and-pki
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Secrets and Identity Automation
secrets-and-identity-automation
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Docker Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Docker id=61 · docker

Aliases — catalog

  • Docker (CANONICAL) primary

Context tags (catalog)

CI/CD Compose DevOps Docker Compose Docker Swarm Dockerfile Kubernetes build pipeline container container lifecycle container orchestration container registry container security containerization containers image image registry images immutable infrastructure lightweight virtualization microservices networking orchestration port mapping registry scalability service discovery swarm volume volume management

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Containerization Tool
Vendor
Docker, Inc.
License
apache_2
Year introduced
2013
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Docker is a hiring-pipeline staple: it appears in many DevOps, backend, and platform JDs, and remains a standard containerization tool alongside Kubernetes in production stacks.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
63
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Containerization and Image Builds Catalog dimension db id 152

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • Deployment and Cloud Platforms Catalog dimension db id 418

    Library dimension (catalog)

    Roles linked in library: Ruby Backend Developer

  • Deployment and Runtime Configuration Catalog dimension db id 13

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Go Backend Developer, PHP Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Containerization and Image Builds
containerization-and-image-builds
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Deployment and Cloud Platforms
deployment-and-cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Deployment and Runtime Configuration
deployment-and-runtime-configuration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Git Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Git id=1002 · git

Aliases — catalog

  • Git (CANONICAL)

Context tags (catalog)

CI/CD GitHub GitLab branching checkout clone commit fork merging pull request rebase remote repository stash versioning

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Version Control Tool
Vendor
Linus Torvalds
License
gpl_v2
Year introduced
2005
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Git is a hiring-pipeline staple: it appears in the vast majority of software engineering job descriptions and is the default VCS on GitHub/GitLab/Bitbucket.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
730
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: CI/CD id=1190 · ci-cd

Aliases — catalog

  • CI/CD (CANONICAL)

Context tags (catalog)

Ansible CircleCI Docker GitLab CI Jenkins Kubernetes Terraform Travis CI automated testing build automation continuous deployment continuous integration deployment pipelines monitoring version control

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Ci Cd Process
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: CI/CD appears in a large share of software engineering JDs and is a standard requirement across DevOps, platform, and backend roles; major vendors like GitHub, GitLab, and AWS all center product roadmaps on CI/CD pipelines.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
900
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • CI/CD Pipeline Platforms Catalog dimension db id 150

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • CI/CD for Machine Learning Catalog dimension db id 56

    Library dimension (catalog)

    Roles linked in library: ML Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure DevOps Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure DevOps id=1214 · azure-devops

Aliases — catalog

  • Azure DevOps (CANONICAL)

Context tags (catalog)

Agile Azure Pipelines Build Agents Continuous Deployment Continuous Integration Docker GitHub Actions Infrastructure as Code Kubernetes Monitoring Release Management Service Hooks Terraform Version Control Work Items

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Devops Platform
Vendor
Microsoft
License
proprietary
Year introduced
2018
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: Azure DevOps appears in many enterprise job descriptions for CI/CD, boards, and repos, and Microsoft continues active product support and updates; it remains a common hiring-pipeline skill alongside GitHub Actions/Jenkins.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
170
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • CI/CD Pipeline Platforms Catalog dimension db id 150

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GitHub Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: GitHub id=280 · github

Aliases — catalog

  • GitHub (CANONICAL) primary

Context tags (catalog)

CI/CD Git GitHub Actions GitHub Enterprise GitHub Pages SSH keys actions branch protection branches code review collaboration commit history fork forking issue tracker issues markdown merge conflicts merge request pull request pull requests release tags repositories repository version control webhooks

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Devops Platform
Vendor
GitHub, Inc.
License
other_open
Year introduced
2008
Confidence
0.96
Version strategy
NOT_APPLICABLE

Maturity reasoning: GitHub appears in a very high volume of engineering JDs for source control, code review, and CI/CD; it’s a standard hiring-pipeline skill across teams.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
170
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • CI/CD Pipeline Platforms Catalog dimension db id 150

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • CI/CD for Machine Learning Catalog dimension db id 56

    Library dimension (catalog)

    Roles linked in library: ML Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Purview Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
Data Governance
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Power BI Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Power BI id=151 · power-bi

Aliases — catalog

  • Power BI (CANONICAL) primary

Context tags (catalog)

Azure Synapse DAX DirectQuery Import mode M language Power Query RLS SQL Server SSAS dashboard data modeling data warehouse gateway reporting star schema

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Bi Analytics Platform
Vendor
Microsoft
License
proprietary
Year introduced
2015
Confidence
0.96
Version strategy
NOT_APPLICABLE

Maturity reasoning: Power BI appears frequently in BI/data analyst job descriptions and is a standard Microsoft analytics platform in enterprise stacks, with strong vendor support and broad adoption.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
111
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • BI and Visualization Tools Catalog dimension db id 31

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
BI and Visualization Tools
bi-and-visualization-tools
Existing dimension (library) · Role↔dimension saved
Azure Machine Learning Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure ML id=212 · azure-ml

Aliases — catalog

  • Azure ML (CANONICAL) primary

Context tags (catalog)

AKS AutoML Azure Databricks Azure DevOps Azure Functions Azure Machine Learning ML Studio MLflow REST API SDK v2 TensorFlow automated ML compute cluster compute instance data labeling data preprocessing datastore designer endpoint deployment feature store hyperparameter tuning model deployment model monitoring model registry notebooks pipeline orchestration pipelines scikit-learn workspace

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Ml Platform
Vendor
Microsoft
License
proprietary
Year introduced
2018
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: Azure ML appears frequently in ML/DS job postings and Microsoft’s Azure AI portfolio, indicating broad enterprise adoption for model training and deployment on Azure.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
175
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • MLOps Platforms and Lifecycle Catalog dimension db id 43

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
MLOps Platforms and Lifecycle
mlops-platforms-and-lifecycle
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Terraform Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Terraform id=286 · terraform

Aliases — catalog

  • Terraform (CANONICAL) primary

Context tags (catalog)

AWS Azure GCP HCL IaC Terraform Cloud Terraform Enterprise Terraform Registry Terragrunt apply backend destroy infrastructure automation modules outputs plan providers provisioning remote backends remote state resource blocks resource management state file state management terraform apply terraform plan variables version control workspaces

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Infrastructure As Code Tool
Vendor
HashiCorp
License
mpl
Year introduced
2014
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: Terraform is broadly listed in DevOps/SRE/cloud JDs and remains a standard IaC tool across AWS/Azure/GCP; HashiCorp’s ecosystem and widespread GitHub usage signal strong market adoption.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
191
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Infrastructure & Security Automation Frameworks Catalog dimension db id 249

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Infrastructure as Code Catalog dimension db id 132

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, DevOps Engineer

  • Infrastructure as Code for ML Catalog dimension db id 57

    Library dimension (catalog)

    Roles linked in library: ML Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Infrastructure & Security Automation Frameworks
infrastructure-security-automation-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Infrastructure as Code
infrastructure-as-code
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Infrastructure as Code for ML
infrastructure-as-code-for-ml
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Bicep Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Bicep id=838 · bicep

Aliases — catalog

  • Bicep (CANONICAL) primary

Context tags (catalog)

ARM templates Azure CI/CD GitHub Actions JSON Terraform YAML declarative deployment infrastructure as code modules outputs parameters resource groups versioning

Stored enrichment (catalog DB)

Category
Language
Sub-category
Infrastructure As Code Language
Vendor
Microsoft
License
mit
Year introduced
2020
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: Azure JDs increasingly list Bicep for ARM replacement, and Microsoft positions it as the recommended IaC language for Azure deployments, but it is still far less common than Terraform/ARM in postings.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
609
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Infrastructure as Code Catalog dimension db id 132

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, DevOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Infrastructure as Code
infrastructure-as-code
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Hugging Face Transformers Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Machine Learning Frameworks
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
PEFT Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: PEFT id=1330 · peft

Aliases — catalog

  • PEFT (CANONICAL) primary

Context tags (catalog)

LoRA adapter tuning domain adaptation efficient training fine-tuning gradient-based methods hyperparameter optimization model compression multi-task learning parameter sharing pre-trained models prompt tuning scalable models task adaptation transfer learning

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Parameter Efficient Fine Tuning Concept
Confidence
0.88
Version strategy
NOT_APPLICABLE

Maturity reasoning: PEFT is increasingly listed in ML/LLM job descriptions and tied to Hugging Face/LoRA workflows, but it is not yet a universal hiring staple like core PyTorch or AWS.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
957
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Model Fine-Tuning & Adaptation Catalog dimension db id 212

    Library dimension (catalog)

    Roles linked in library: AI Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Model Fine-Tuning & Adaptation
model-fine-tuning-adaptation
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
LoRA Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: LoRA id=1328 · lora

Aliases — catalog

  • LoRA (CANONICAL) primary

Context tags (catalog)

NLP attention mechanisms deep learning fine-tuning gradient descent hyperparameter tuning low-rank adaptation model compression multi-task learning parameter efficiency pre-trained models task adaptation training efficiency transfer learning transformers

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Parameter Efficient Fine Tuning Concept
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: LoRA is increasingly listed in ML/LLM job descriptions and widely used in open-source fine-tuning stacks, but it is still a specialized concept rather than a universal hiring staple.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
957
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Model Fine-Tuning & Adaptation Catalog dimension db id 212

    Library dimension (catalog)

    Roles linked in library: AI Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Model Fine-Tuning & Adaptation
model-fine-tuning-adaptation
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: React id=610 · react

Aliases — catalog

  • React (CANONICAL) primary
  • React 0.13 (VERSION)
  • React 0.14 (VERSION)
  • React 15 (VERSION)
  • React 15.x (VERSION)
  • React 16 (VERSION)
  • React 16.x (VERSION)
  • React 17 (VERSION)
  • React 17.x (VERSION)
  • React 18 (VERSION)
  • React 18.x (VERSION)
  • React 19 (VERSION)
  • React v15 (VERSION)
  • React v16 (VERSION)
  • React v17 (VERSION)
  • React v18 (VERSION)
  • React v19 (VERSION)
  • ReactJS 18 (VERSION)
  • react 15 (VERSION)
  • react 16 (VERSION)
  • react 17 (VERSION)
  • react 18 (VERSION)
  • react 19 (VERSION)
  • react15 (VERSION)
  • react16 (VERSION)
  • react17 (VERSION)
  • react18 (VERSION)
  • react19 (VERSION)
  • reactjs 18 (VERSION)

Context tags (catalog)

Babel Class Components Component Lifecycle Context API Functional Components Higher-Order Components Hooks JSX Next.js PropTypes Props React Native React Router Redux SSR State Management Styled Components Testing Library TypeScript Virtual DOM Webpack component lifecycle context API frontend hooks props state management useEffect useState virtual DOM

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Frontend Framework
Vendor
Meta
License
mit
Year introduced
2013
Confidence
0.98
Version strategy
SEPARATE_ENTITY
Version tag
18

Maturity reasoning: React appears in high-volume frontend job postings across startups and enterprises and remains a default hiring-pipeline skill, with strong GitHub/npm usage and ecosystem activity.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
1072
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Application Frameworks & Libraries Catalog dimension db id 451

    Library dimension (catalog)

    Roles linked in library: Sitecore Dev

  • Frameworks & Libraries Catalog dimension db id 360

    Library dimension (catalog)

    Roles linked in library: Drupal Dev, Engineering Manager

  • Frontend Frameworks and Libraries Catalog dimension db id 434

    Library dimension (catalog)

    Roles linked in library: Shopify Dev

  • JavaScript for WordPress Catalog dimension db id 329

    Library dimension (catalog)

    Roles linked in library: WordPress Dev

  • React Component Architecture Catalog dimension db id 302

    Library dimension (catalog)

    Roles linked in library: React Frontend Developer

  • UI Frameworks and Rendering Catalog dimension db id 115

    Library dimension (catalog)

    Roles linked in library: Frontend Developer, Fullstack Developer, Fullstack Developer, Hybrid Mobile Developer, Ionic Developer, Web Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Application Frameworks & Libraries
application-frameworks-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Frameworks & Libraries
frameworks-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Frontend Frameworks and Libraries
frontend-frameworks-and-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JavaScript for WordPress
javascript-for-wordpress
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React Component Architecture
react-component-architecture
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
UI Frameworks and Rendering
ui-frameworks-and-rendering
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Angular Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Angular id=612 · angular

Aliases — catalog

  • Angular (CANONICAL) primary
  • Angular 1 (VERSION)
  • Angular 1.x (VERSION)
  • Angular 10 (VERSION)
  • Angular 11 (VERSION)
  • Angular 12 (VERSION)
  • Angular 13 (VERSION)
  • Angular 14 (VERSION)
  • Angular 15 (VERSION)
  • Angular 16 (VERSION)
  • Angular 17 (VERSION)
  • Angular 2 (VERSION)
  • Angular 2+ (VERSION)
  • Angular 4 (VERSION)
  • Angular 5 (VERSION)
  • Angular 6 (VERSION)
  • Angular 7 (VERSION)
  • Angular 8 (VERSION)
  • Angular 9 (VERSION)
  • AngularJS (VERSION)
  • angular 1 (VERSION)
  • angular 1.x (VERSION)
  • angular 10 (VERSION)
  • angular 11 (VERSION)
  • angular 12 (VERSION)
  • angular 13 (VERSION)
  • angular 14 (VERSION)
  • angular 15 (VERSION)
  • angular 16 (VERSION)
  • angular 17 (VERSION)
  • angular 18 (VERSION)
  • angular 19 (VERSION)
  • angular 2 (VERSION)
  • angular 2+ (VERSION)
  • angular 2.x (VERSION)
  • angular 3 (VERSION)
  • angular 4 (VERSION)
  • angular 5 (VERSION)
  • angular 6 (VERSION)
  • angular 7 (VERSION)
  • angular 8 (VERSION)
  • angular 9 (VERSION)
  • angular17 (VERSION)
  • angular2 (VERSION)
  • angularjs (VERSION)
  • angularjs 1.x (VERSION)
  • ng (VERSION)
  • ng1 (VERSION)
  • ng2 (VERSION)

Context tags (catalog)

AOT Angular CLI Angular Material Component Dependency Injection Directive NgRx Observable Observables PWA RESTful services Reactive Forms Routing RxJS Service Single Page Application TypeScript Unit Testing component-based components dependency injection directives lazy loading modules observables pipes responsive design routing services single-page application single-page applications templates two-way data binding unit testing

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Frontend Framework
Vendor
Google
License
mit
Year introduced
2010
Confidence
0.98
Version strategy
SEPARATE_ENTITY
Version tag
2+

Maturity reasoning: Angular remains widely listed in frontend job descriptions and enterprise stacks; Google continues maintaining Angular, and it is a common hiring-pipeline skill alongside React/Vue rather than a sunset technology.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
1072
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Angular Component Model and Templates Catalog dimension db id 303

    Library dimension (catalog)

    Roles linked in library: Angular Frontend Developer

  • Application Frameworks & Libraries Catalog dimension db id 451

    Library dimension (catalog)

    Roles linked in library: Sitecore Dev

  • Frameworks & Libraries Catalog dimension db id 360

    Library dimension (catalog)

    Roles linked in library: Drupal Dev, Engineering Manager

  • UI Frameworks and Rendering Catalog dimension db id 115

    Library dimension (catalog)

    Roles linked in library: Frontend Developer, Fullstack Developer, Fullstack Developer, Hybrid Mobile Developer, Ionic Developer, Web Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Angular Component Model and Templates
angular-component-model-and-templates
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Application Frameworks & Libraries
application-frameworks-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Frameworks & Libraries
frameworks-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
UI Frameworks and Rendering
ui-frameworks-and-rendering
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
LLMOps Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: LLMOps id=1634 · llmops

Aliases — catalog

  • LLMOps (CANONICAL)

Context tags (catalog)

A/B testing API integration CI/CD MLOps cloud infrastructure containerization data pipelines inference model deployment model management monitoring orchestration performance tuning scalability versioning

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Llm Operations Methodology
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: LLMOps appears increasingly in job descriptions and vendor docs for deploying and monitoring LLM apps, but it is not yet a universal hiring staple like AWS/Kubernetes.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
1232
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Experiment Tracking and Evaluation Catalog dimension db id 44

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • Guardrails and Safety Controls Catalog dimension db id 203

    Library dimension (catalog)

    Roles linked in library: AI Engineer

  • LLM Serving & Deployment Catalog dimension db id 209

    Library dimension (catalog)

    Roles linked in library: AI Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Experiment Tracking and Evaluation
experiment-tracking-and-evaluation
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Guardrails and Safety Controls
guardrails-and-safety-controls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
LLM Serving & Deployment
llm-serving-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
MLOps Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: MLOps id=1196 · mlops

Aliases — catalog

  • MLOps (CANONICAL)

Context tags (catalog)

A/B testing CI/CD Docker Kubeflow Kubernetes MLflow automation cloud-native data governance data pipeline model deployment monitoring reproducibility scalability versioning

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Mlops
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: MLOps appears in many job descriptions for ML/platform roles and is a standard practice in major cloud vendor docs (AWS, GCP, Azure) for CI/CD, model monitoring, and deployment.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
906
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • CI/CD for Machine Learning Catalog dimension db id 56

    Library dimension (catalog)

    Roles linked in library: ML Engineer

  • Data Lineage and Metadata Catalog dimension db id 28

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Deployment Rollouts and Release Control Catalog dimension db id 51

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Data Lineage and Metadata
data-lineage-and-metadata
Existing dimension (library) · Role↔dimension saved
Deployment Rollouts and Release Control
deployment-rollouts-and-release-control
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure OpenAI Service Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure OpenAI id=1187 · azure-openai

Aliases — catalog

  • Azure OpenAI (CANONICAL) primary

Context tags (catalog)

AI integration API integration API management Azure Cognitive Services Azure DevOps Azure Functions Azure Machine Learning ChatGPT GPT-3 cost management cost optimization data preprocessing machine learning model deployment natural language processing prompt engineering real-time analytics scalability security compliance

Stored enrichment (catalog DB)

Category
Service
Sub-category
Managed Llm Service
Vendor
Microsoft
License
proprietary
Year introduced
2021
Confidence
0.95
Version strategy
NOT_APPLICABLE

Maturity reasoning: Appears increasingly in job descriptions for GenAI/LLM roles and Azure architecture stacks, but is still far less universal than core cloud services like AWS/Azure. Microsoft’s rapid product expansion signals growing adoption.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
1007
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer

  • LLM Provider APIs Catalog dimension db id 195

    Library dimension (catalog)

    Roles linked in library: AI Engineer

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
LLM Provider APIs
llm-provider-apis
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
React Frontend Development
d_init_01
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Azure OpenAI Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure OpenAI id=1187 · azure-openai

Aliases — catalog

  • Azure OpenAI (CANONICAL) primary

Context tags (catalog)

AI integration API integration API management Azure Cognitive Services Azure DevOps Azure Functions Azure Machine Learning ChatGPT GPT-3 cost management cost optimization data preprocessing machine learning model deployment natural language processing prompt engineering real-time analytics scalability security compliance

Stored enrichment (catalog DB)

Category
Service
Sub-category
Managed Llm Service
Vendor
Microsoft
License
proprietary
Year introduced
2021
Confidence
0.95
Version strategy
NOT_APPLICABLE

Maturity reasoning: Appears increasingly in job descriptions for GenAI/LLM roles and Azure architecture stacks, but is still far less universal than core cloud services like AWS/Azure. Microsoft’s rapid product expansion signals growing adoption.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
1007
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer

  • LLM Provider APIs Catalog dimension db id 195

    Library dimension (catalog)

    Roles linked in library: AI Engineer

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
LLM Provider APIs
llm-provider-apis
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure AI services Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
AI and Machine Learning
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure Cognitive Search Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure Cognitive Search id=4169 · azure-cognitive-search

Aliases — catalog

  • Azure Cognitive Search (CANONICAL) primary

Context tags (catalog)

AI enrichment Azure portal REST API autocomplete cognitive skills data sources facets indexers indexing querying scoring profiles search algorithms search index search suggestions synonyms

Stored enrichment (catalog DB)

Category
Service
Sub-category
Search Service
Vendor
Microsoft
License
other_open
Year introduced
2017
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: Frequently appears in Azure/cloud job descriptions and Microsoft positions it as a core managed search service, with broad enterprise adoption for app search and RAG retrieval.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
3308
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Search and Content Discovery Catalog dimension db id 356

    Library dimension (catalog)

    Roles linked in library: Drupal Dev, Sitecore Dev

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Search and Content Discovery
search-and-content-discovery
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure AI Search Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure Cognitive Search id=4169 · azure-cognitive-search

Aliases — catalog

  • Azure Cognitive Search (CANONICAL) primary

Context tags (catalog)

AI enrichment Azure portal REST API autocomplete cognitive skills data sources facets indexers indexing querying scoring profiles search algorithms search index search suggestions synonyms

Stored enrichment (catalog DB)

Category
Service
Sub-category
Search Service
Vendor
Microsoft
License
other_open
Year introduced
2017
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: Frequently appears in Azure/cloud job descriptions and Microsoft positions it as a core managed search service, with broad enterprise adoption for app search and RAG retrieval.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
3308
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Search and Content Discovery Catalog dimension db id 356

    Library dimension (catalog)

    Roles linked in library: Drupal Dev, Sitecore Dev

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Search and Content Discovery
search-and-content-discovery
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
LangChain Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: LangChain id=240 · langchain

Aliases — catalog

  • LangChain (CANONICAL) primary

Context tags (catalog)

API integration Hugging Face LLM LLMs OpenAI RAG agents callbacks chains data augmentation deployment document loaders embeddings fine-tuning memory prompt engineering prompt templates prompts retrieval retrievers state management streaming text splitters toolkits tools vector database vector stores

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Llm Application Framework
Vendor
Harrison Chase
License
mit
Year introduced
2022
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: LangChain appears in many recent AI/LLM job postings and is widely used in app prototypes, but it’s still not a universal hiring staple like React or AWS.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
146
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • LLM Operations and Orchestration Catalog dimension db id 49

    Library dimension (catalog)

    Roles linked in library: AI Engineer, ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
LLM Operations and Orchestration
llm-operations-and-orchestration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
LlamaIndex Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: LlamaIndex id=244 · llamaindex

Aliases — catalog

  • LlamaIndex (CANONICAL) primary
  • llama-index (VERSION)
  • llamaindex (VERSION)
  • llamaindex 0.10 (VERSION)
  • llamaindex 0.9 (VERSION)
  • llamaindex v0.10 (VERSION)
  • llamaindex v0.9 (VERSION)

Context tags (catalog)

API integration API support Hugging Face LLM integration LLM orchestration LangChain OpenAI RAG chunking custom data sources data connectors data indexing data pipelines document indexing document loaders document loading embedding embedding models embeddings fine-tuning indexing knowledge base knowledge graphs metadata management performance tuning prompt engineering prompt templates query engine query optimization querying real-time analytics real-time indexing retrieval-augmented generation retrievers scalability search optimization semantic search vector database vector databases vector store

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Llm Application Framework
Vendor
LlamaIndex
License
unknown
Year introduced
2023
Confidence
0.97
Version strategy
SEPARATE_ENTITY
Version tag
0.10

Maturity reasoning: LlamaIndex appears in growing numbers of LLM/RAG job postings and vendor docs, but it is still far less common than Python or LangChain, indicating rising adoption rather than universal demand.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
146
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • LLM Operations and Orchestration Catalog dimension db id 49

    Library dimension (catalog)

    Roles linked in library: AI Engineer, ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
LLM Operations and Orchestration
llm-operations-and-orchestration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
FastAPI Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: FastAPI id=1201 · fastapi

Aliases — catalog

  • FastAPI (CANONICAL) primary

Context tags (catalog)

API documentation ASGI CORS JSON JSON Schema OAuth2 OpenAPI Pydantic RESTful Starlette UVicorn WebSocket async async programming data validation dependency injection middleware path parameters query parameters type hints uvicorn

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Web Framework
Vendor
Sebastián Ramírez
License
mit
Year introduced
2018
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: FastAPI appears in many Python backend job postings and has strong GitHub adoption; it’s now a common choice for API development alongside Flask/Django rather than a niche tool.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
35
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Web Application Frameworks Catalog dimension db id 2

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer, Java Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Web Application Frameworks
web-application-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Flask Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Flask id=1344 · flask

Aliases — catalog

  • Flask (CANONICAL) primary
  • flask 2 (VERSION)
  • flask 2.x (VERSION)
  • flask 3 (VERSION)
  • flask 3.x (VERSION)
  • flask2 (VERSION)
  • flask3 (VERSION)
  • flask>=3 (VERSION)

Context tags (catalog)

API Blueprints Flask-Migrate Flask-RESTful Flask-SQLAlchemy Flask-WTF JSON Jinja2 RESTful RESTful APIs SQLAlchemy Werkzeug debugging deployment gunicorn middleware routing session management template rendering unit testing virtual environments virtualenv

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Web Framework
Vendor
Pallets Projects
License
bsd
Year introduced
2010
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
3.x

Maturity reasoning: Flask appears in many Python web developer job postings and remains a common lightweight framework in hiring pipelines, though often alongside Django/FastAPI rather than as a niche tool.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
35
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Web Application Frameworks Catalog dimension db id 2

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer, Java Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Web Application Frameworks
web-application-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Django Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Django id=9 · django

Aliases — catalog

  • Django (CANONICAL) primary
  • Django 1 (VERSION)
  • Django 1.x (VERSION)
  • Django 2 (VERSION)
  • Django 2.x (VERSION)
  • Django 3 (VERSION)
  • Django 3.x (VERSION)
  • Django 4 (VERSION)
  • Django 4.x (VERSION)
  • Django 5 (VERSION)
  • Django 5.x (VERSION)
  • Django1 (VERSION)
  • Django2 (VERSION)
  • Django3 (VERSION)
  • Django4 (VERSION)
  • Django5 (VERSION)
  • django 2 (VERSION)
  • django 2.x (VERSION)
  • django 3 (VERSION)
  • django 3.x (VERSION)
  • django 4 (VERSION)
  • django 4.x (VERSION)
  • django 5 (VERSION)
  • django 5.0 (VERSION)
  • django 5.x (VERSION)
  • django2 (VERSION)
  • django2.x (VERSION)
  • django3 (VERSION)
  • django3.x (VERSION)
  • django4 (VERSION)
  • django4.x (VERSION)
  • django5 (VERSION)
  • django5.0 (VERSION)
  • django5.x (VERSION)

Context tags (catalog)

Celery Django REST Framework Django Signals Jinja2 MVT ORM PostgreSQL QuerySet REST URL routing admin interface admin site authentication celery csrf deployment forms gunicorn middleware migrations models pytest querysets settings signals static files templates views

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Web Framework
Vendor
Django Software Foundation
License
bsd
Year introduced
2005
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
5

Maturity reasoning: Django appears in many backend web job descriptions and remains a standard Python web framework; its GitHub ecosystem and long-term LTS releases show sustained market demand.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
35
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Frameworks & Libraries Catalog dimension db id 360

    Library dimension (catalog)

    Roles linked in library: Drupal Dev, Engineering Manager

  • Web Application Frameworks Catalog dimension db id 2

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer, Java Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Frameworks & Libraries
frameworks-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Web Application Frameworks
web-application-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Functions Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure Functions id=1462 · azure-functions

Aliases — catalog

  • Azure Functions (CANONICAL) primary

Context tags (catalog)

API Management Azure DevOps Azure Event Grid Azure Logic Apps Azure Storage C# Cosmos DB HTTP triggers JavaScript PowerShell cost optimization deployment slots durable functions event-driven function app microservices monitoring scalability serverless serverless architecture

Stored enrichment (catalog DB)

Category
Service
Sub-category
Serverless Compute Service
Vendor
Microsoft
License
proprietary
Year introduced
2016
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Broadly listed in cloud/serverless job descriptions and Microsoft actively supports it as a core Azure service; it’s a common hiring-pipeline skill for event-driven apps and APIs.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
1097
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms & Hosting Providers Catalog dimension db id 278

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Kotlin Backend Developer, Scala Backend Developer, Web Developer

  • Cloud Platforms & Managed Services Catalog dimension db id 221

    Library dimension (catalog)

    Roles linked in library: Fullstack Developer, Go Backend Developer, Node.js Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure App Service Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure App Service id=518 · azure-app-service

Aliases — catalog

  • Azure App Service (CANONICAL) primary

Context tags (catalog)

API Apps API Management App Insights App Service Plan Application Insights Authentication Azure CLI Azure DevOps Azure Functions Azure Portal CI/CD Continuous Deployment Custom Domains Deployment Slots DevOps Kudu Linux App Service Monitoring Resource Group Resource Groups SSL Certificates Scaling Serverless TLS/SSL Web App Web Apps Windows App Service autoscale custom domain deployment slots managed identity slot swap

Stored enrichment (catalog DB)

Category
Service
Sub-category
Application Hosting Service
Vendor
Microsoft
License
proprietary
Year introduced
2015
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Broadly listed in cloud/platform JDs and Microsoft positions it as a core PaaS for web apps and APIs; it remains a common hiring-pipeline skill alongside Azure.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
1702
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer

  • Cloud Platforms & Hosting Providers Catalog dimension db id 278

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Kotlin Backend Developer, Scala Backend Developer, Web Developer

  • Cloud Platforms & Managed Services Catalog dimension db id 221

    Library dimension (catalog)

    Roles linked in library: Fullstack Developer, Go Backend Developer, Node.js Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AKS Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: AKS id=1221 · aks

Aliases — catalog

  • AKS (CANONICAL)

Context tags (catalog)

Azure CI/CD DevOps Helm Kubernetes container registry containerization kubectl load balancing microservices monitoring network policies persistent storage scalability service mesh

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Kubernetes Platform
Vendor
Microsoft
License
other_open
Year introduced
2018
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: AKS appears frequently in cloud/Kubernetes job descriptions and Microsoft actively markets it as a core Azure service, indicating broad enterprise adoption rather than niche use.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
927
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Container Orchestration Platforms Catalog dimension db id 134

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, DevOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Container Orchestration Platforms
container-orchestration-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
REST Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: REST id=11 · rest

Aliases — catalog

  • REST (CANONICAL) primary

Context tags (catalog)

API API design API versioning CRUD DELETE GET HATEOAS HTTP JSON OAuth OAuth2 OpenAPI POST PUT Postman RESTful Swagger URI Webhooks XML authentication client-server content negotiation endpoint endpoints middleware resource resource-oriented serialization stateless status codes versioning web services

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Api Architecture Style
Year introduced
2000
Confidence
0.88
Version strategy
NOT_APPLICABLE

Maturity reasoning: REST is a default API architecture in many job descriptions and is widely supported by major vendors/frameworks; OpenAPI and RESTful endpoints remain standard in hiring pipelines.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
2122
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • API Design and Contracts Catalog dimension db id 3

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer, Fullstack Developer

  • API Interface and Contract Design Catalog dimension db id 289

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Go Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer

  • Integration Protocols & Standards Catalog dimension db id 271

    Library dimension (catalog)

    Roles linked in library: Pega Developer

  • Standards, Protocols & Compliance Catalog dimension db id 452

    Library dimension (catalog)

    Roles linked in library: Engineering Manager, Sitecore Dev

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
API Design and Contracts
api-design-and-contracts
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
API Interface and Contract Design
api-interface-and-contract-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Integration Protocols & Standards
integration-protocols-standards
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Standards, Protocols & Compliance
standards-protocols-compliance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SharePoint Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
Collaboration
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Microsoft 365 Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Cloud Platforms
Sub-category
Productivity
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
AWS Bedrock Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: AWS Bedrock id=1208 · aws-bedrock

Aliases — catalog

  • AWS Bedrock (CANONICAL)

Context tags (catalog)

API integration SageMaker cloud-native cost optimization data pipelines data security deployment foundation models generative AI inference machine learning model training multi-modal real-time analytics scalability serverless architecture

Stored enrichment (catalog DB)

Category
Service
Sub-category
Foundation Model Service
Vendor
Amazon Web Services
License
proprietary
Year introduced
2023
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: AWS Bedrock is appearing in more job descriptions and vendor docs as teams adopt managed LLM APIs, but it is still far less common than core AWS services like EC2/S3 or Kubernetes in hiring pipelines.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
915
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Vertex AI Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Vertex AI id=210 · vertex-ai

Aliases — catalog

  • Vertex AI (CANONICAL) primary

Context tags (catalog)

AI pipelines AI solutions AutoML BigQuery Feature Store Kubeflow ML Ops MLOps Model Registry PyTorch TensorFlow Vertex AI Pipelines Vertex AI Workbench Vertex Pipelines cloud training custom models data labeling endpoint deployment hyperparameter tuning integration model training notebooks prediction prediction service scalability training jobs

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Ml Platform
Vendor
Google
License
proprietary
Year introduced
2021
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: Vertex AI appears in growing numbers of ML/AI job postings and Google Cloud docs, but JD volume is still below AWS SageMaker/Azure ML, indicating rising adoption rather than universal demand.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
EMERGING
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
175
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • MLOps Platforms and Lifecycle Catalog dimension db id 43

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
MLOps Platforms and Lifecycle
mlops-platforms-and-lifecycle
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

All API 3 persistence rows

Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.

Skill Tag Dimension Skill↔dim Role↔dim Outcome Notes
Azure Synapse Analytics in_db
Cloud Data Warehouses
cloud-data-warehouses
Existing dimension (library) · Role↔dimension saved
Databricks in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Storage new
Cloud Storage and Data Services
cloud-storage-and-data-services
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Azure Storage new
Cloud Storage and File Formats
cloud-storage-and-file-formats
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
PySpark new
ETL and ELT Tooling
etl-and-elt-tooling
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Python in_db
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Python in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL in_db
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL in_db
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Kafka in_db
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kafka in_db
Messaging and Background Jobs
messaging-and-background-jobs
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Kafka in_db
Messaging and Event Streaming
messaging-and-event-streaming
Existing dimension (library) · Role↔dimension saved
Delta Lake in_db
Model and Data Versioning
model-and-data-versioning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Lakehouse Architecture new
React Frontend Development
d_init_01
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Azure AD in_db
Identity and Access Architecture
identity-and-access-architecture
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure AD in_db
Identity and Access Management Products
identity-and-access-management-products
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
RBAC in_db
Authentication and Authorization
authentication-and-authorization
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
RBAC in_db
Backend Authentication and Authorization
backend-authentication-and-authorization
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Key Vault in_db
Cryptography and PKI
cryptography-and-pki
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Key Vault in_db
Secrets and Identity Automation
secrets-and-identity-automation
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Docker in_db
Containerization and Image Builds
containerization-and-image-builds
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Docker in_db
Deployment and Cloud Platforms
deployment-and-cloud-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Docker in_db
Deployment and Runtime Configuration
deployment-and-runtime-configuration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Git in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD in_db
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD in_db
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure DevOps in_db
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GitHub in_db
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GitHub in_db
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Power BI in_db
BI and Visualization Tools
bi-and-visualization-tools
Existing dimension (library) · Role↔dimension saved
Azure Machine Learning new
MLOps Platforms and Lifecycle
mlops-platforms-and-lifecycle
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Terraform in_db
Infrastructure & Security Automation Frameworks
infrastructure-security-automation-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Terraform in_db
Infrastructure as Code
infrastructure-as-code
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Terraform in_db
Infrastructure as Code for ML
infrastructure-as-code-for-ml
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Bicep in_db
Infrastructure as Code
infrastructure-as-code
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
PEFT in_db
Model Fine-Tuning & Adaptation
model-fine-tuning-adaptation
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
LoRA in_db
Model Fine-Tuning & Adaptation
model-fine-tuning-adaptation
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React in_db
Application Frameworks & Libraries
application-frameworks-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React in_db
Frameworks & Libraries
frameworks-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React in_db
Frontend Frameworks and Libraries
frontend-frameworks-and-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React in_db
JavaScript for WordPress
javascript-for-wordpress
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React in_db
React Component Architecture
react-component-architecture
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React in_db
UI Frameworks and Rendering
ui-frameworks-and-rendering
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Angular in_db
Angular Component Model and Templates
angular-component-model-and-templates
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Angular in_db
Application Frameworks & Libraries
application-frameworks-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Angular in_db
Frameworks & Libraries
frameworks-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Angular in_db
UI Frameworks and Rendering
ui-frameworks-and-rendering
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
LLMOps in_db
Experiment Tracking and Evaluation
experiment-tracking-and-evaluation
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
LLMOps in_db
Guardrails and Safety Controls
guardrails-and-safety-controls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
LLMOps in_db
LLM Serving & Deployment
llm-serving-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
MLOps in_db
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
MLOps in_db
Data Lineage and Metadata
data-lineage-and-metadata
Existing dimension (library) · Role↔dimension saved
MLOps in_db
Deployment Rollouts and Release Control
deployment-rollouts-and-release-control
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure OpenAI Service new
Cloud Platforms
cloud-platforms
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Azure OpenAI Service new
LLM Provider APIs
llm-provider-apis
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Azure OpenAI Service new
React Frontend Development
d_init_01
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Azure OpenAI in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Azure OpenAI in_db
LLM Provider APIs
llm-provider-apis
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure OpenAI in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Cognitive Search in_db
Search and Content Discovery
search-and-content-discovery
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure AI Search new
Search and Content Discovery
search-and-content-discovery
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
LangChain in_db
LLM Operations and Orchestration
llm-operations-and-orchestration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
LlamaIndex in_db
LLM Operations and Orchestration
llm-operations-and-orchestration
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
FastAPI in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
FastAPI in_db
Web Application Frameworks
web-application-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Flask in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Flask in_db
Web Application Frameworks
web-application-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Django in_db
Frameworks & Libraries
frameworks-libraries
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Django in_db
Web Application Frameworks
web-application-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Functions in_db
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Functions in_db
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure App Service in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Azure App Service in_db
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure App Service in_db
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AKS in_db
Container Orchestration Platforms
container-orchestration-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
REST in_db
API Design and Contracts
api-design-and-contracts
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
REST in_db
API Interface and Contract Design
api-interface-and-contract-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
REST in_db
Integration Protocols & Standards
integration-protocols-standards
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
REST in_db
Standards, Protocols & Compliance
standards-protocols-compliance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS Bedrock in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Vertex AI in_db
MLOps Platforms and Lifecycle
mlops-platforms-and-lifecycle
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Azure Data Factory | type=Cloud Platforms subtype=Data Integration nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Azure Synapse Pipelines | type=Cloud Platforms subtype=Data Integration nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Azure Databricks | type=Cloud Platforms subtype=Data Engineering nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed ADLS Gen2 | type=Cloud Platforms subtype=Storage nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Azure Event Hubs | type=Cloud Platforms subtype=Messaging nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Azure Stream Analytics | type=Cloud Platforms subtype=Data Streaming nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Managed Identities | type=Cloud Platforms subtype=Security nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Azure Purview | type=Cloud Platforms subtype=Data Governance nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Hugging Face Transformers | type=Machine Learning Frameworks subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Azure AI services | type=Cloud Platforms subtype=AI and Machine Learning nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed SharePoint | type=Cloud Platforms subtype=Collaboration nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Microsoft 365 | type=Cloud Platforms subtype=Productivity nature=PLATFORM lifespan=MULTI_YEAR
dimension_skill_link_proposed Azure Storage ↔ Cloud Storage and Data Services
dimension_skill_link_proposed Azure Storage ↔ Cloud Storage and File Formats
role_dimension_link_proposed Data Engineer ↔ Cloud Storage and File Formats
dimension_skill_link_proposed PySpark ↔ ETL and ELT Tooling
role_dimension_link_proposed Data Engineer ↔ ETL and ELT Tooling
dimension_skill_link_proposed Lakehouse Architecture ↔ React Frontend Development
dimension_skill_link_proposed Azure Machine Learning ↔ MLOps Platforms and Lifecycle
dimension_skill_link_proposed Azure OpenAI Service ↔ Cloud Platforms
role_dimension_link_proposed Data Engineer ↔ Cloud Platforms
dimension_skill_link_proposed Azure OpenAI Service ↔ LLM Provider APIs
dimension_skill_link_proposed Azure OpenAI Service ↔ React Frontend Development
dimension_skill_link_proposed Azure AI Search ↔ Search and Content Discovery
nano JD Parser — gpt-4.1-nano click to toggle
RoleSenior Associate
CompanyPwC
Experience4-7
DomainIT Services & Consulting
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": {
    "source_marker": {
      "first_5_words": "At PwC, our people in",
      "last_5_words": "software products and solutions."
    },
    "text": "At PwC, our people in software and product innovation focus on developing cutting-edge software solutions and driving product innovation to meet the evolving needs of clients. These individuals combine technical experience with creative thinking to deliver innovative software products and solutions.",
    "word_count": 42
  },
  "archetype_override_applied": true,
  "archetype_override_matched_skills": [
    "Python",
    "LLMOps",
    "Docker",
    "Metadata management",
    "Power BI",
    "Azure Synapse Analytics",
    "RAG",
    "GitHub",
    "RBAC",
    "Microsoft Azure",
    "Make",
    "Bicep",
    "DevOps",
    "MLOps",
    "Prompt engineering",
    "OpenAI",
    "AWS Bedrock",
    "Monitoring",
    "Chatbots",
    "Azure OpenAI",
    "Hugging Face",
    "Git",
    "CI/CD",
    "FastAPI",
    "Frontend",
    "Databricks",
    "AKS",
    "APIs",
    "Analytics",
    "Azure DevOps",
    "LoRA",
    "Lakehouse",
    "PEFT",
    "Machine Learning",
    "Artificial Intelligence",
    "Data Lakes",
    "Azure",
    "Azure Functions",
    "Vertex AI",
    "Delta Lake",
    "LangChain",
    "LlamaIndex",
    "API",
    "Cloud",
    "Terraform",
    "Flask",
    "Azure AD",
    "Azure Key Vault",
    "REST",
    "microservices",
    "Edge",
    "components",
    "SQL",
    "AWS",
    "Django",
    "indexing",
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API 1 — extract-from-jd click to toggle
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            "sentence": "Azure Data Factory, Azure Synapse Analytics, Azure Databricks, ADLS Gen2, Azure Storage, PySpark, Python, SQL, Data Warehousing, ETL/ELT, Data Modeling, Azure SQL / SQL MI, Azure OpenAI Service, Azure Cognitive Services, Azure Cognitive Search / Azure AI Search, LangChain, LlamaIndex, REST API Development (FastAPI/Flask/Django), Azure Functions, Azure App Service, Azure AD, Managed Identities, RBAC, Azure Key Vault, Encryption, Docker, Git, CI/CD (Azure DevOps/GitHub).",
            "similarity": 0.4581
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 12,
        "score": 0.5025,
        "slug": "ai-compliance-officer",
        "total_count": null
      },
      {
        "display_name": "MLOps Engineer",
        "kra_matches": [
          {
            "kra_text": "Automates ML platform operations including scheduled retraining triggers, pipeline orchestration, evaluation workflows, and alerting configuration.",
            "sentence": "Azure Event Hubs, Kafka, Azure Stream Analytics, Delta Lake / Lakehouse Architecture, Azure Purview, Power BI Integration, Azure Machine Learning, Azure OpenAI Integration, Terraform / Bicep, Cost Optimization on Azure Data Services, Real-time Analytics, Hugging Face Transformers, PEFT / LoRA Fine-tuning, Multi-cloud GenAI Platforms (Azure OpenAI / AWS Bedrock / Vertex AI), Prompt Engineering Techniques, Frontend Integration (React / Angular) for chatbots, LLMOps / MLOps, Monitoring \u0026 Logging for GenAI, Security \u0026 Compliance for AI workloads.",
            "similarity": 0.5231
          },
          {
            "kra_text": "Automates ML platform operations including scheduled retraining triggers, pipeline orchestration, evaluation workflows, and alerting configuration.",
            "sentence": "Design and implement scalable data ingestion and transformation pipelines using Azure Data Factory, Azure Synapse Pipelines, Databricks, and serverless compute; build and manage data lakes and lakehouse architectures using ADLS, Delta Lake, and enterprise Azure warehouse components; develop PySpark/Python data processing jobs for batch and streaming; implement real-time ingestion with Azure Event Hubs, Azure Stream Analytics, or Kafka; apply best practices for data modeling, partitioning, indexing, compression, cost optimization, and performance tuning across Azure platforms; ensure data quality, lineage, metadata management, and auditing across the lifecycle; implement security and governance with Azure AD, Managed Identities, Key Vault, network isolation, and fine-grained RBAC; design and develop GenAI applications using Azure OpenAI and Azure AI services; implement RAG architectures using Azure Cognitive Search / Azure AI Search and Azure data stores; integrate GenAI solutions with ADLS, Synapse, SQL, SharePoint, and Microsoft 365; build Python APIs, microservices, and backends with FastAPI/Flask hosted on Azure Functions, App Service, or AKS; implement prompt.",
            "similarity": 0.4771
          },
          {
            "kra_text": "Automates ML platform operations including scheduled retraining triggers, pipeline orchestration, evaluation workflows, and alerting configuration.",
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          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 16,
        "score": 0.4883,
        "slug": "ml-ops-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": 9,
        "matched_skills": [
          "Azure App Service",
          "Azure OpenAI",
          "Docker",
          "FastAPI",
          "Flask",
          "Kafka",
          "Python",
          "RBAC",
          "REST"
        ],
        "role_id": 1,
        "score": 0.25,
        "slug": "backend-engineer",
        "total_count": 36
      },
      {
        "display_name": "Python Backend Developer",
        "kra_matches": null,
        "matched_count": 8,
        "matched_skills": [
          "Azure App Service",
          "Azure OpenAI",
          "FastAPI",
          "Flask",
          "Kafka",
          "Python",
          "RBAC",
          "REST"
        ],
        "role_id": 80,
        "score": 0.2222,
        "slug": "python-backend-developer",
        "total_count": 36
      },
      {
        "display_name": "Node.js Backend Developer",
        "kra_matches": null,
        "matched_count": 8,
        "matched_skills": [
          "Azure App Service",
          "Azure Functions",
          "Azure OpenAI",
          "FastAPI",
          "Flask",
          "Kafka",
          "RBAC",
          "REST"
        ],
        "role_id": 82,
        "score": 0.2222,
        "slug": "node-backend-developer",
        "total_count": 36
      },
      {
        "display_name": "DevOps Engineer",
        "kra_matches": null,
        "matched_count": 8,
        "matched_skills": [
          "AKS",
          "Azure App Service",
          "Azure DevOps",
          "Azure Key Vault",
          "Azure OpenAI",
          "CI/CD",
          "Docker",
          "GitHub"
        ],
        "role_id": 10,
        "score": 0.2222,
        "slug": "devops-engineer",
        "total_count": 36
      },
      {
        "display_name": "Fullstack Developer",
        "kra_matches": null,
        "matched_count": 7,
        "matched_skills": [
          "Azure App Service",
          "Azure Functions",
          "Azure OpenAI",
          "FastAPI",
          "Flask",
          "Python",
          "REST"
        ],
        "role_id": 15,
        "score": 0.1944,
        "slug": "full-stack-engineer",
        "total_count": 36
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "DOMAIN",
    "chosen_role": {
      "display_name": "Data Engineer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 2,
      "score": 0.98,
      "slug": "data-engineer",
      "total_count": null
    },
    "confidence": 0.98,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [
      "Data Pipeline Engineering",
      "Lakehouse Architecture",
      "Batch and Streaming Data Processing",
      "Real-time Data Ingestion",
      "Data Modeling and Performance Tuning",
      "Data Quality and Governance",
      "Azure Security and Access Control",
      "GenAI Application Development"
    ],
    "matched_kras": [
      "Design and implement scalable data ingestion and transformation pipelines",
      "Build and manage data lakes and lakehouse architectures",
      "Develop PySpark/Python data processing jobs for batch and streaming",
      "Implement real-time ingestion with Azure Event Hubs",
      "Apply best practices for data modeling, partitioning, indexing, compression",
      "Ensure data quality, lineage, metadata management, and auditing",
      "Implement security and governance with Azure AD, Managed Identities",
      "Design and develop GenAI applications using Azure OpenAI"
    ],
    "matched_skills": [
      "Azure Data Factory",
      "Azure Synapse Pipelines",
      "Databricks",
      "ADLS",
      "Delta Lake",
      "PySpark",
      "Python",
      "Azure Event Hubs",
      "Azure Stream Analytics",
      "Kafka",
      "Azure OpenAI",
      "Azure Cognitive Search",
      "FastAPI",
      "Flask",
      "Azure Functions"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=Data Engineering \u0026 Analytics; The JD is primarily for a cloud data engineer building Azure-based ingestion, transformation, lakehouse, streaming, and pipeline solutions, with additional GenAI and API work.",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 493,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 22969,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Azure Data Factory",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 22970,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Azure Synapse Pipelines",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 22971,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Azure Databricks",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 22972,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "ADLS Gen2",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 22973,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Azure Storage",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 22974,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "PySpark",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 22975,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Azure Event Hubs",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 22976,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Azure Stream Analytics",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 22977,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Lakehouse Architecture",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 22978,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Managed Identities",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 22979,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Azure Purview",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 22980,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Azure Machine Learning",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 22982,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Hugging Face Transformers",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 22984,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Azure OpenAI Service",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 22986,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Azure AI services",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 22988,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Azure AI Search",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 22992,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "SharePoint",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 22993,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Microsoft 365",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
API 2 — extract-details
{
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      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 302,
      "existing_alias_text": "Azure Synapse Analytics",
      "input_term": "Azure Synapse Analytics",
      "matched_canonical": {
        "category_id": 11,
        "display_name": "Azure Synapse Analytics",
        "id": 108,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CLOUD_SERVICE",
        "slug": "azure-synapse-analytics",
        "sub_category_id": 117,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1838,
      "existing_alias_text": "Databricks",
      "input_term": "Databricks",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "Databricks",
        "id": 1202,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "databricks",
        "sub_category_id": 911,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 381,
      "existing_alias_text": "Azure Blob Storage",
      "input_term": "Azure Storage",
      "matched_canonical": {
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        "display_name": "Azure Blob Storage",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CLOUD_SERVICE",
        "slug": "azure-blob-storage",
        "sub_category_id": 120,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 2004,
      "existing_alias_text": "Apache Spark",
      "input_term": "PySpark",
      "matched_canonical": {
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "FRAMEWORK",
        "slug": "apache-spark",
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        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 67,
      "existing_alias_text": "Python",
      "input_term": "Python",
      "matched_canonical": {
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        "display_name": "Python",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "python",
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        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
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      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 271,
      "existing_alias_text": "SQL",
      "input_term": "SQL",
      "matched_canonical": {
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
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        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
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      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 173,
      "existing_alias_text": "Kafka",
      "input_term": "Kafka",
      "matched_canonical": {
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
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        "sub_category_id": 3533,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 498,
      "existing_alias_text": "Delta Lake",
      "input_term": "Delta Lake",
      "matched_canonical": {
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        "display_name": "Delta Lake",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "delta-lake",
        "sub_category_id": 1170,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": null,
      "existing_alias_text": null,
      "input_term": "Lakehouse Architecture",
      "matched_canonical": {
        "category_id": 1,
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        "id": 1359,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PATTERN",
        "slug": "lakehouse",
        "sub_category_id": 1026,
        "typical_lifespan": "EVERGREEN",
        "volatility": "EMERGING"
      },
      "matched_via": "embedding_display_name"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 658,
      "existing_alias_text": "Azure AD",
      "input_term": "Azure AD",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "Azure AD",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "azure-ad",
        "sub_category_id": 784,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 166,
      "existing_alias_text": "RBAC",
      "input_term": "RBAC",
      "matched_canonical": {
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        "display_name": "RBAC",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "rbac",
        "sub_category_id": 5,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1435,
      "existing_alias_text": "Azure Key Vault",
      "input_term": "Azure Key Vault",
      "matched_canonical": {
        "category_id": 11,
        "display_name": "Azure Key Vault",
        "id": 873,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CLOUD_SERVICE",
        "slug": "azure-key-vault",
        "sub_category_id": 644,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 198,
      "existing_alias_text": "Docker",
      "input_term": "Docker",
      "matched_canonical": {
        "category_id": 13,
        "display_name": "Docker",
        "id": 61,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "docker",
        "sub_category_id": 63,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1613,
      "existing_alias_text": "Git",
      "input_term": "Git",
      "matched_canonical": {
        "category_id": 13,
        "display_name": "Git",
        "id": 1002,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "git",
        "sub_category_id": 730,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1826,
      "existing_alias_text": "CI/CD",
      "input_term": "CI/CD",
      "matched_canonical": {
        "category_id": 8,
        "display_name": "CI/CD",
        "id": 1190,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "ci-cd",
        "sub_category_id": 900,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1850,
      "existing_alias_text": "Azure DevOps",
      "input_term": "Azure DevOps",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "Azure DevOps",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "azure-devops",
        "sub_category_id": 170,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 541,
      "existing_alias_text": "GitHub",
      "input_term": "GitHub",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "GitHub",
        "id": 280,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "github",
        "sub_category_id": 170,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 360,
      "existing_alias_text": "Power BI",
      "input_term": "Power BI",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "Power BI",
        "id": 151,
        "is_also_category": false,
        "is_extractable": true,
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    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "dimensions": [
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Data Warehouses",
        "id": 22,
        "rationale": "Managed analytical storage and compute platforms used for curated datasets, reporting, and downstream analytics. These systems are central to data modeling, performance tuning, and cost-aware query design.",
        "slug": "cloud-data-warehouses",
        "source": "db"
      },
      "input_skill": "Azure Synapse Analytics",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "Databricks",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Storage and Data Services",
        "id": 144,
        "rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
        "slug": "cloud-storage-and-data-services",
        "source": "db"
      },
      "input_skill": "Azure Storage",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Storage and File Formats",
        "id": 35,
        "rationale": "Object storage and data file formats used as the physical substrate for data movement and lake-style analytics. Data engineers need these to manage landing zones, partitioned datasets, and efficient interchange.",
        "slug": "cloud-storage-and-file-formats",
        "source": "db"
      },
      "input_skill": "Azure Storage",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "ETL and ELT Tooling",
        "id": 24,
        "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
        "slug": "etl-and-elt-tooling",
        "source": "db"
      },
      "input_skill": "PySpark",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Security Scripting \u0026 DSL Languages",
        "id": 248,
        "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
        "slug": "cloud-security-scripting-dsl-languages",
        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Security Engineer",
          "id": 23,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages",
        "id": 1,
        "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
        "slug": "programming-languages",
        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Backend Developer",
          "id": 1,
          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
          "source": "db"
        },
        {
          "display_name": "Fullstack Developer",
          "id": 15,
          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
          "source": "db"
        },
        {
          "display_name": "Fullstack Developer",
          "id": 435,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "fullstack-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages \u0026 DSLs",
        "id": 475,
        "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
        "slug": "programming-languages-dsls",
        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Engineering Manager",
          "id": 121,
          "rationale": null,
          "role_archetype": null,
          "slug": "engineering-manager",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages and Scripting",
        "id": 59,
        "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
        "slug": "programming-languages-and-scripting",
        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cyber Security Engineer",
          "id": 5,
          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages for Data Work",
        "id": 21,
        "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
        "slug": "programming-languages-for-data-work",
        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages for ML Systems",
        "id": 39,
        "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
        "slug": "programming-languages-for-ml-systems",
        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "MLOps Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages for XR",
        "id": 97,
        "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
        "slug": "programming-languages-for-xr",
        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "AR/VR Engineer",
          "id": 8,
          "rationale": null,
          "role_archetype": null,
          "slug": "ar-vr-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Python Programming",
        "id": 290,
        "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
        "slug": "python-programming",
        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Python Backend Developer",
          "id": 80,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "python-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Pega Programming Languages \u0026 DSLs",
        "id": 267,
        "rationale": "Programming languages and domain-specific languages used in Pega development.",
        "slug": "pega-programming-languages-dsls",
        "source": "db"
      },
      "input_skill": "SQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Pega Developer",
          "id": 24,
          "rationale": null,
          "role_archetype": null,
          "slug": "pega-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages \u0026 DSLs",
        "id": 475,
        "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
        "slug": "programming-languages-dsls",
        "source": "db"
      },
      "input_skill": "SQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Engineering Manager",
          "id": 121,
          "rationale": null,
          "role_archetype": null,
          "slug": "engineering-manager",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages for Data Work",
        "id": 21,
        "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
        "slug": "programming-languages-for-data-work",
        "source": "db"
      },
      "input_skill": "SQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Asynchronous Messaging and Event Streaming",
        "id": 297,
        "rationale": "Asynchronous communication patterns and broker technologies used to decouple backend services and move work off the request path. Includes queues, pub/sub, event streams, consumer groups, dead-letter queues, and delivery semantics across systems such as Kafka, RabbitMQ, NATS, SQS/SNS, Pulsar, and ActiveMQ.",
        "slug": "asynchronous-messaging-and-event-streaming",
        "source": "db"
      },
      "input_skill": "Kafka",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": ".NET Backend Developer",
          "id": 83,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "dotnet-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Go Backend Developer",
          "id": 81,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "go-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Kotlin Backend Developer",
          "id": 84,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "kotlin-server-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Node.js Backend Developer",
          "id": 82,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Scala Backend Developer",
          "id": 87,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "scala-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Messaging and Background Jobs",
        "id": 291,
        "rationale": "Asynchronous processing patterns and worker systems used to decouple backend work from request handling. This is a coherent cluster because the role supports background jobs, retries, and deferred processing.",
        "slug": "messaging-and-background-jobs",
        "source": "db"
      },
      "input_skill": "Kafka",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "PHP Backend Developer",
          "id": 86,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "php-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Python Backend Developer",
          "id": 80,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "python-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Ruby Backend Developer",
          "id": 85,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "ruby-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Messaging and Event Streaming",
        "id": 8,
        "rationale": "Transport-layer systems used to move events and decouple producers from consumers. Data engineers use these systems to ingest, buffer, and distribute event data before downstream processing.",
        "slug": "messaging-and-event-streaming",
        "source": "db"
      },
      "input_skill": "Kafka",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Backend Developer",
          "id": 1,
          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
          "source": "db"
        },
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Model and Data Versioning",
        "id": 48,
        "rationale": "Versioning systems for datasets, features, and model artifacts at the storage layer. This enables reproducible training, rollback, lineage of artifacts, and controlled promotion of model assets.",
        "slug": "model-and-data-versioning",
        "source": "db"
      },
      "input_skill": "Delta Lake",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "MLOps Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "Lakehouse Architecture",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Identity and Access Architecture",
        "id": 137,
        "rationale": "Cloud identity patterns for authentication, authorization, federation, and privileged access boundaries. This is central to cloud governance because it defines who can administer and consume platform resources.",
        "slug": "identity-and-access-architecture",
        "source": "db"
      },
      "input_skill": "Azure AD",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
          "source": "db"
        },
        {
          "display_name": "Cloud Security Engineer",
          "id": 23,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Identity and Access Management Products",
        "id": 65,
        "rationale": "Identity platforms and privileged access tools used to enforce authentication, authorization, and administrative control. This is a vendor-family dimension because the role often reviews multiple IAM and PAM products in enterprise environments.",
        "slug": "identity-and-access-management-products",
        "source": "db"
      },
      "input_skill": "Azure AD",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cyber Security Engineer",
          "id": 5,
          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Authentication and Authorization",
        "id": 6,
        "rationale": "Identity, session, and access-control mechanisms used to protect PHP backend resources. This includes login flows, token handling, role checks, permissions, and policy enforcement in server-side code.",
        "slug": "authentication-and-authorization",
        "source": "db"
      },
      "input_skill": "RBAC",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": ".NET Backend Developer",
          "id": 83,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "dotnet-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Backend Developer",
          "id": 1,
          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
          "source": "db"
        },
        {
          "display_name": "Go Backend Developer",
          "id": 81,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "go-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Java Backend Developer",
          "id": 79,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "java-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Node.js Backend Developer",
          "id": 82,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
        },
        {
          "display_name": "PHP Backend Developer",
          "id": 86,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "php-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Python Backend Developer",
          "id": 80,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "python-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Backend Authentication and Authorization",
        "id": 386,
        "rationale": "Identity and access control mechanisms used by backend services to authenticate users or clients and enforce permissions on protected resources. This includes token and session handling, OAuth 2.0 / OpenID Connect / SAML flows, JWT and access tokens, API keys, MFA, role- or claim-based authorization, RBAC/ABAC, scopes, policies, Spring Security, and authorization filters.",
        "slug": "backend-authentication-and-authorization",
        "source": "db"
      },
      "input_skill": "RBAC",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Kotlin Backend Developer",
          "id": 84,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "kotlin-server-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Ruby Backend Developer",
          "id": 85,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "ruby-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Scala Backend Developer",
          "id": 87,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "scala-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cryptography and PKI",
        "id": 67,
        "rationale": "Cryptographic primitives and trust infrastructure used to protect data, identities, and communications. This is a coherent cluster because the role needs to reason about keys, certificates, signatures, and protocol internals when reviewing controls.",
        "slug": "cryptography-and-pki",
        "source": "db"
      },
      "input_skill": "Azure Key Vault",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Security Engineer",
          "id": 23,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
          "source": "db"
        },
        {
          "display_name": "Cyber Security Engineer",
          "id": 5,
          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Secrets and Identity Automation",
        "id": 154,
        "rationale": "Operational handling of credentials, service identities, and access tokens used by delivery systems and runtime environments. This cluster is coherent because release pipelines and deployment targets depend on secure machine-to-machine access.",
        "slug": "secrets-and-identity-automation",
        "source": "db"
      },
      "input_skill": "Azure Key Vault",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "DevOps Engineer",
          "id": 10,
          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
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        "display_name": "Application Frameworks \u0026 Libraries",
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        "rationale": "Covers the primary software frameworks and libraries often used alongside Sitecore for building and enhancing site experiences.",
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      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Manage adoption, integration, and best practices around key software frameworks and libraries.",
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      "input_skill": "Angular",
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          "rationale": null,
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          "display_name": "Engineering Manager",
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        "display_name": "UI Frameworks and Rendering",
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        "rationale": "Component frameworks and rendering models used to build browser screens, reusable UI, and interactive client flows. This is a core cluster because frontend engineers spend much of their time composing and updating view hierarchies.",
        "slug": "ui-frameworks-and-rendering",
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      "input_skill": "Angular",
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          "display_name": "Fullstack Developer",
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          "rationale": null,
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          "slug": "ionic-developer",
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          "display_name": "Web Developer",
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        "rationale": "Tools and practices for recording experiments, comparing runs, and assessing model quality before release. This dimension focuses on reproducibility, metrics, artifacts, and offline evaluation workflows.",
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        "rationale": "Runtime controls that constrain model behavior, block unsafe outputs, and enforce product policy. This is a core AI Engineer responsibility because the role owns fallback behavior, refusal logic, and safe response shaping in production.",
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          "slug": "ai-engineer",
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    },
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              "id": 82,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "node-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Python Backend Developer",
              "id": 80,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "python-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Scala Backend Developer",
              "id": 87,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "scala-backend-developer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "AWS Bedrock",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Vertex AI",
          "alias_type": "CANONICAL",
          "id": 462,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 9,
        "display_name": "Vertex AI",
        "id": 210,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "vertex-ai",
        "sub_category_id": 175,
        "typical_lifespan": "EVERGREEN",
        "volatility": "EMERGING"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "MLOps Platforms and Lifecycle",
            "id": 43,
            "rationale": "End-to-end managed platforms used to train, deploy, register, and govern models across their lifecycle. This is the operational control plane for production ML workflows.",
            "slug": "mlops-platforms-and-lifecycle",
            "source": "db"
          },
          "input_skill": "Vertex AI",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Vertex AI",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Azure Data Factory",
    "Azure Synapse Pipelines",
    "Azure Databricks",
    "ADLS Gen2",
    "Azure Event Hubs",
    "Azure Stream Analytics",
    "Managed Identities",
    "Azure Purview",
    "Hugging Face Transformers",
    "Azure AI services",
    "SharePoint",
    "Microsoft 365"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD is primarily for a cloud data engineer building Azure-based ingestion, transformation, lakehouse, streaming, and pipeline solutions, with additional GenAI and API work.",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Azure Data Factory",
      "tag": "new"
    },
    {
      "skill": "Azure Synapse Analytics",
      "tag": "in_db"
    },
    {
      "skill": "Azure Synapse Pipelines",
      "tag": "new"
    },
    {
      "skill": "Azure Databricks",
      "tag": "new"
    },
    {
      "skill": "Databricks",
      "tag": "in_db"
    },
    {
      "skill": "ADLS Gen2",
      "tag": "new"
    },
    {
      "skill": "Azure Storage",
      "tag": "in_db"
    },
    {
      "skill": "PySpark",
      "tag": "in_db"
    },
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "Azure Event Hubs",
      "tag": "new"
    },
    {
      "skill": "Azure Stream Analytics",
      "tag": "new"
    },
    {
      "skill": "Kafka",
      "tag": "in_db"
    },
    {
      "skill": "Delta Lake",
      "tag": "in_db"
    },
    {
      "skill": "Lakehouse Architecture",
      "tag": "in_db"
    },
    {
      "skill": "Azure AD",
      "tag": "in_db"
    },
    {
      "skill": "Managed Identities",
      "tag": "new"
    },
    {
      "skill": "RBAC",
      "tag": "in_db"
    },
    {
      "skill": "Azure Key Vault",
      "tag": "in_db"
    },
    {
      "skill": "Docker",
      "tag": "in_db"
    },
    {
      "skill": "Git",
      "tag": "in_db"
    },
    {
      "skill": "CI/CD",
      "tag": "in_db"
    },
    {
      "skill": "Azure DevOps",
      "tag": "in_db"
    },
    {
      "skill": "GitHub",
      "tag": "in_db"
    },
    {
      "skill": "Azure Purview",
      "tag": "new"
    },
    {
      "skill": "Power BI",
      "tag": "in_db"
    },
    {
      "skill": "Azure Machine Learning",
      "tag": "in_db"
    },
    {
      "skill": "Terraform",
      "tag": "in_db"
    },
    {
      "skill": "Bicep",
      "tag": "in_db"
    },
    {
      "skill": "Hugging Face Transformers",
      "tag": "new"
    },
    {
      "skill": "PEFT",
      "tag": "in_db"
    },
    {
      "skill": "LoRA",
      "tag": "in_db"
    },
    {
      "skill": "React",
      "tag": "in_db"
    },
    {
      "skill": "Angular",
      "tag": "in_db"
    },
    {
      "skill": "LLMOps",
      "tag": "in_db"
    },
    {
      "skill": "MLOps",
      "tag": "in_db"
    },
    {
      "skill": "Azure OpenAI Service",
      "tag": "in_db"
    },
    {
      "skill": "Azure OpenAI",
      "tag": "in_db"
    },
    {
      "skill": "Azure AI services",
      "tag": "new"
    },
    {
      "skill": "Azure Cognitive Search",
      "tag": "in_db"
    },
    {
      "skill": "Azure AI Search",
      "tag": "in_db"
    },
    {
      "skill": "LangChain",
      "tag": "in_db"
    },
    {
      "skill": "LlamaIndex",
      "tag": "in_db"
    },
    {
      "skill": "FastAPI",
      "tag": "in_db"
    },
    {
      "skill": "Flask",
      "tag": "in_db"
    },
    {
      "skill": "Django",
      "tag": "in_db"
    },
    {
      "skill": "Azure Functions",
      "tag": "in_db"
    },
    {
      "skill": "Azure App Service",
      "tag": "in_db"
    },
    {
      "skill": "AKS",
      "tag": "in_db"
    },
    {
      "skill": "REST",
      "tag": "in_db"
    },
    {
      "skill": "SharePoint",
      "tag": "new"
    },
    {
      "skill": "Microsoft 365",
      "tag": "new"
    },
    {
      "skill": "AWS Bedrock",
      "tag": "in_db"
    },
    {
      "skill": "Vertex AI",
      "tag": "in_db"
    }
  ],
  "llm_cost_api1_usd": null,
  "llm_cost_api2_usd": null,
  "llm_cost_api3_usd": null,
  "llm_cost_total_usd": null,
  "persistence": {
    "items": [
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Data Warehouses",
          "id": 22,
          "rationale": "Managed analytical storage and compute platforms used for curated datasets, reporting, and downstream analytics. These systems are central to data modeling, performance tuning, and cost-aware query design.",
          "slug": "cloud-data-warehouses",
          "source": "db"
        },
        "dimension_id": 22,
        "input_skill": "Azure Synapse Analytics",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 108,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Databricks",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1202,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Storage and Data Services",
          "id": 144,
          "rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
          "slug": "cloud-storage-and-data-services",
          "source": "db"
        },
        "dimension_id": 144,
        "input_skill": "Azure Storage",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Storage and File Formats",
          "id": 35,
          "rationale": "Object storage and data file formats used as the physical substrate for data movement and lake-style analytics. Data engineers need these to manage landing zones, partitioned datasets, and efficient interchange.",
          "slug": "cloud-storage-and-file-formats",
          "source": "db"
        },
        "dimension_id": 35,
        "input_skill": "Azure Storage",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "ETL and ELT Tooling",
          "id": 24,
          "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
          "slug": "etl-and-elt-tooling",
          "source": "db"
        },
        "dimension_id": 24,
        "input_skill": "PySpark",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Scripting \u0026 DSL Languages",
          "id": 248,
          "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
          "slug": "cloud-security-scripting-dsl-languages",
          "source": "db"
        },
        "dimension_id": 248,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages",
          "id": 1,
          "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
          "slug": "programming-languages",
          "source": "db"
        },
        "dimension_id": 1,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 435,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "fullstack-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages \u0026 DSLs",
          "id": 475,
          "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
          "slug": "programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 475,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages and Scripting",
          "id": 59,
          "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
          "slug": "programming-languages-and-scripting",
          "source": "db"
        },
        "dimension_id": 59,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for Data Work",
          "id": 21,
          "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
        "dimension_id": 21,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for ML Systems",
          "id": 39,
          "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
          "slug": "programming-languages-for-ml-systems",
          "source": "db"
        },
        "dimension_id": 39,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for XR",
          "id": 97,
          "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
          "slug": "programming-languages-for-xr",
          "source": "db"
        },
        "dimension_id": 97,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AR/VR Engineer",
            "id": 8,
            "rationale": null,
            "role_archetype": null,
            "slug": "ar-vr-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Python Programming",
          "id": 290,
          "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
          "slug": "python-programming",
          "source": "db"
        },
        "dimension_id": 290,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Pega Programming Languages \u0026 DSLs",
          "id": 267,
          "rationale": "Programming languages and domain-specific languages used in Pega development.",
          "slug": "pega-programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 267,
        "input_skill": "SQL",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Pega Developer",
            "id": 24,
            "rationale": null,
            "role_archetype": null,
            "slug": "pega-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages \u0026 DSLs",
          "id": 475,
          "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
          "slug": "programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 475,
        "input_skill": "SQL",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for Data Work",
          "id": 21,
          "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
        "dimension_id": 21,
        "input_skill": "SQL",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Asynchronous Messaging and Event Streaming",
          "id": 297,
          "rationale": "Asynchronous communication patterns and broker technologies used to decouple backend services and move work off the request path. Includes queues, pub/sub, event streams, consumer groups, dead-letter queues, and delivery semantics across systems such as Kafka, RabbitMQ, NATS, SQS/SNS, Pulsar, and ActiveMQ.",
          "slug": "asynchronous-messaging-and-event-streaming",
          "source": "db"
        },
        "dimension_id": 297,
        "input_skill": "Kafka",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 36,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Messaging and Background Jobs",
          "id": 291,
          "rationale": "Asynchronous processing patterns and worker systems used to decouple backend work from request handling. This is a coherent cluster because the role supports background jobs, retries, and deferred processing.",
          "slug": "messaging-and-background-jobs",
          "source": "db"
        },
        "dimension_id": 291,
        "input_skill": "Kafka",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "PHP Backend Developer",
            "id": 86,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "php-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Ruby Backend Developer",
            "id": 85,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "ruby-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 36,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Messaging and Event Streaming",
          "id": 8,
          "rationale": "Transport-layer systems used to move events and decouple producers from consumers. Data engineers use these systems to ingest, buffer, and distribute event data before downstream processing.",
          "slug": "messaging-and-event-streaming",
          "source": "db"
        },
        "dimension_id": 8,
        "input_skill": "Kafka",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 36,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Model and Data Versioning",
          "id": 48,
          "rationale": "Versioning systems for datasets, features, and model artifacts at the storage layer. This enables reproducible training, rollback, lineage of artifacts, and controlled promotion of model assets.",
          "slug": "model-and-data-versioning",
          "source": "db"
        },
        "dimension_id": 48,
        "input_skill": "Delta Lake",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 237,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Lakehouse Architecture",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Identity and Access Architecture",
          "id": 137,
          "rationale": "Cloud identity patterns for authentication, authorization, federation, and privileged access boundaries. This is central to cloud governance because it defines who can administer and consume platform resources.",
          "slug": "identity-and-access-architecture",
          "source": "db"
        },
        "dimension_id": 137,
        "input_skill": "Azure AD",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Architect",
            "id": 9,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-architect",
            "source": "db"
          },
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 342,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Identity and Access Management Products",
          "id": 65,
          "rationale": "Identity platforms and privileged access tools used to enforce authentication, authorization, and administrative control. This is a vendor-family dimension because the role often reviews multiple IAM and PAM products in enterprise environments.",
          "slug": "identity-and-access-management-products",
          "source": "db"
        },
        "dimension_id": 65,
        "input_skill": "Azure AD",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 342,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Authentication and Authorization",
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          "rationale": "Identity, session, and access-control mechanisms used to protect PHP backend resources. This includes login flows, token handling, role checks, permissions, and policy enforcement in server-side code.",
          "slug": "authentication-and-authorization",
          "source": "db"
        },
        "dimension_id": 6,
        "input_skill": "RBAC",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
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          },
          {
            "display_name": "Backend Developer",
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            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
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          },
          {
            "display_name": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Java Backend Developer",
            "id": 79,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "PHP Backend Developer",
            "id": 86,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "php-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 29,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Backend Authentication and Authorization",
          "id": 386,
          "rationale": "Identity and access control mechanisms used by backend services to authenticate users or clients and enforce permissions on protected resources. This includes token and session handling, OAuth 2.0 / OpenID Connect / SAML flows, JWT and access tokens, API keys, MFA, role- or claim-based authorization, RBAC/ABAC, scopes, policies, Spring Security, and authorization filters.",
          "slug": "backend-authentication-and-authorization",
          "source": "db"
        },
        "dimension_id": 386,
        "input_skill": "RBAC",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Ruby Backend Developer",
            "id": 85,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "ruby-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
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            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 29,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cryptography and PKI",
          "id": 67,
          "rationale": "Cryptographic primitives and trust infrastructure used to protect data, identities, and communications. This is a coherent cluster because the role needs to reason about keys, certificates, signatures, and protocol internals when reviewing controls.",
          "slug": "cryptography-and-pki",
          "source": "db"
        },
        "dimension_id": 67,
        "input_skill": "Azure Key Vault",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          },
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 873,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Secrets and Identity Automation",
          "id": 154,
          "rationale": "Operational handling of credentials, service identities, and access tokens used by delivery systems and runtime environments. This cluster is coherent because release pipelines and deployment targets depend on secure machine-to-machine access.",
          "slug": "secrets-and-identity-automation",
          "source": "db"
        },
        "dimension_id": 154,
        "input_skill": "Azure Key Vault",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 873,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Containerization and Image Builds",
          "id": 152,
          "rationale": "Container image creation, tagging, hardening, and registry workflows used to package services for deployment. This is coherent because DevOps often owns the build-to-image path that feeds runtime environments.",
          "slug": "containerization-and-image-builds",
          "source": "db"
        },
        "dimension_id": 152,
        "input_skill": "Docker",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 61,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Deployment and Cloud Platforms",
          "id": 418,
          "rationale": "Platform-as-a-Service and container environments for deploying Ruby applications.",
          "slug": "deployment-and-cloud-platforms",
          "source": "db"
        },
        "dimension_id": 418,
        "input_skill": "Docker",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Ruby Backend Developer",
            "id": 85,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "ruby-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 61,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Deployment and Runtime Configuration",
          "id": 13,
          "rationale": "Configuration and release artifacts that control how backend services run in environments. Includes environment variables, manifests, feature flags, and release-safe configuration management.",
          "slug": "deployment-and-runtime-configuration",
          "source": "db"
        },
        "dimension_id": 13,
        "input_skill": "Docker",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "PHP Backend Developer",
            "id": 86,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "php-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 61,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Git",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1002,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD Pipeline Platforms",
          "id": 150,
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        "skill_dimension_saved": true,
        "skill_id": 610,
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        "roles_from_db": [
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            "role_archetype": "Engineering",
            "slug": "shopify-dev",
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        ],
        "skill_dimension_saved": true,
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            "display_name": "WordPress Dev",
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [
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            "slug": "frontend-engineer",
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            "display_name": "Ionic Developer",
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          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 612,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Frameworks \u0026 Libraries",
          "id": 360,
          "rationale": "Manage adoption, integration, and best practices around key software frameworks and libraries.",
          "slug": "frameworks-libraries",
          "source": "db"
        },
        "dimension_id": 360,
        "input_skill": "Angular",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Drupal Dev",
            "id": 228,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "drupal-dev",
            "source": "db"
          },
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 612,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "UI Frameworks and Rendering",
          "id": 115,
          "rationale": "Component frameworks and rendering models used to build browser screens, reusable UI, and interactive client flows. This is a core cluster because frontend engineers spend much of their time composing and updating view hierarchies.",
          "slug": "ui-frameworks-and-rendering",
          "source": "db"
        },
        "dimension_id": 115,
        "input_skill": "Angular",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Frontend Developer",
            "id": 7,
            "rationale": null,
            "role_archetype": null,
            "slug": "frontend-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 435,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "fullstack-developer",
            "source": "db"
          },
          {
            "display_name": "Hybrid Mobile Developer",
            "id": 11,
            "rationale": null,
            "role_archetype": null,
            "slug": "hybrid-mobile-developer",
            "source": "db"
          },
          {
            "display_name": "Ionic Developer",
            "id": 434,
            "rationale": null,
            "role_archetype": null,
            "slug": "ionic-developer",
            "source": "db"
          },
          {
            "display_name": "Web Developer",
            "id": 25,
            "rationale": null,
            "role_archetype": null,
            "slug": "web-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 612,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Experiment Tracking and Evaluation",
          "id": 44,
          "rationale": "Tools and practices for recording experiments, comparing runs, and assessing model quality before release. This dimension focuses on reproducibility, metrics, artifacts, and offline evaluation workflows.",
          "slug": "experiment-tracking-and-evaluation",
          "source": "db"
        },
        "dimension_id": 44,
        "input_skill": "LLMOps",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1634,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Guardrails and Safety Controls",
          "id": 203,
          "rationale": "Runtime controls that constrain model behavior, block unsafe outputs, and enforce product policy. This is a core AI Engineer responsibility because the role owns fallback behavior, refusal logic, and safe response shaping in production.",
          "slug": "guardrails-and-safety-controls",
          "source": "db"
        },
        "dimension_id": 203,
        "input_skill": "LLMOps",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AI Engineer",
            "id": 13,
            "rationale": null,
            "role_archetype": null,
            "slug": "ai-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1634,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "LLM Serving \u0026 Deployment",
          "id": 209,
          "rationale": "Tools and frameworks for hosting and serving LLM models in production environments.",
          "slug": "llm-serving-deployment",
          "source": "db"
        },
        "dimension_id": 209,
        "input_skill": "LLMOps",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AI Engineer",
            "id": 13,
            "rationale": null,
            "role_archetype": null,
            "slug": "ai-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1634,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD for Machine Learning",
          "id": 56,
          "rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
          "slug": "ci-cd-for-machine-learning",
          "source": "db"
        },
        "dimension_id": 56,
        "input_skill": "MLOps",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1196,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Data Lineage and Metadata",
          "id": 28,
          "rationale": "Cataloging, documenting, and tracing how data moves and changes across systems. This dimension supports impact analysis, governance, discoverability, and operational understanding of datasets.",
          "slug": "data-lineage-and-metadata",
          "source": "db"
        },
        "dimension_id": 28,
        "input_skill": "MLOps",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1196,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Deployment Rollouts and Release Control",
          "id": 51,
          "rationale": "Practices for safely promoting models through environments and managing rollback when production behavior changes. This dimension covers release gating, version pinning, and rollout strategies specific to ML systems.",
          "slug": "deployment-rollouts-and-release-control",
          "source": "db"
        },
        "dimension_id": 51,
        "input_skill": "MLOps",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1196,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms",
          "id": 20,
          "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
          "slug": "cloud-platforms",
          "source": "db"
        },
        "dimension_id": 20,
        "input_skill": "Azure OpenAI Service",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          },
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Java Backend Developer",
            "id": 79,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
          },
          {
            "display_name": "ML Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "LLM Provider APIs",
          "id": 195,
          "rationale": "Direct integration with hosted model APIs used to generate, classify, extract, and transform content. This is the primary vendor surface for shipping AI features because it determines model choice, request shape, streaming, tool use, and cost/latency tradeoffs.",
          "slug": "llm-provider-apis",
          "source": "db"
        },
        "dimension_id": 195,
        "input_skill": "Azure OpenAI Service",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AI Engineer",
            "id": 13,
            "rationale": null,
            "role_archetype": null,
            "slug": "ai-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Azure OpenAI Service",
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        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms",
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          "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
          "slug": "cloud-platforms",
          "source": "db"
        },
        "dimension_id": 20,
        "input_skill": "Azure OpenAI",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          },
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          },
          {
            "display_name": "DevOps Engineer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
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            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Java Backend Developer",
            "id": 79,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
          },
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
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          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "LLM Provider APIs",
          "id": 195,
          "rationale": "Direct integration with hosted model APIs used to generate, classify, extract, and transform content. This is the primary vendor surface for shipping AI features because it determines model choice, request shape, streaming, tool use, and cost/latency tradeoffs.",
          "slug": "llm-provider-apis",
          "source": "db"
        },
        "dimension_id": 195,
        "input_skill": "Azure OpenAI",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AI Engineer",
            "id": 13,
            "rationale": null,
            "role_archetype": null,
            "slug": "ai-engineer",
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          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Azure OpenAI",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1187,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Search and Content Discovery",
          "id": 356,
          "rationale": "Implementing site search, indexing, and content discovery features in Drupal. This cluster is coherent because many Drupal sites need structured search experiences beyond basic navigation.",
          "slug": "search-and-content-discovery",
          "source": "db"
        },
        "dimension_id": 356,
        "input_skill": "Azure Cognitive Search",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Drupal Dev",
            "id": 228,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "drupal-dev",
            "source": "db"
          },
          {
            "display_name": "Sitecore Dev",
            "id": 233,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "sitecore-dev",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 4169,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
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}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

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