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Pipeline run

3672c1d8-ab5e-4e9d-90e2-0b01f267ee7e

Pipeline LLM cost (USD)
API 1: $0.0040 API 2: $0.0004 API 3: $0.0000 Total: $0.0044

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 transformation and modeling
Build and tune Azure-based batch and real-time data pipelines, transform/model large datasets from multiple sources, and validate new sources for accuracy. Also document best practices and support BI-ready outputs under tight timelines.
""Ability to work on various aspects of Data transformations and Data Modelling.""
Tech stack maturity
Mainstream Modern
The stack centers on widely adopted cloud and data-engineering technologies such as Azure, Spark, Kafka, Docker, and Python, indicating a modern but not cutting-edge cloud-native profile.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
0.20 / 5
· Title match
Has AI skill
· AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3): Machine Learning
Evidence — skills matched in JD (20)
Azure Data Factory Apache Spark Kafka ETL ARM templates Azure IoT Data Streaming Python R MongoDB Cosmos DB Power BI Tableau Docker DevOps Dash Plotly D3.js Datawrapper
Skill cluster (8 dimension groups, role-scoped)
BI and Visualization Tools
Power BI Tableau
CI/CD Pipeline Platforms
DevOps
Cloud Platforms
Azure
Containerization and Image Builds
Docker
ETL and ELT Tooling
Apache Spark
Messaging and Event Streaming
Kafka
Programming Languages for Data Work
Python
Cross-cutting / unaligned
Data Factory ETL ARM templates Azure IoT Data Streaming R MongoDB Cosmos DB Dash Plotly D3.js Datawrapper
Show KRA description ↓
• Building data pipelines and applying data transformations for batch and real-time messaging systems. • Assessing the effectiveness and accuracy of new data sources and data gathering techniques. • Ability to work on various aspects of Data transformations and Data Modelling. • Enhancing data collection procedures to include information that is relevant for building analytic systems. • Following and documenting best practices and processes. • Demonstrating the ability to handle multiple assignments in parallel. • Meeting aggressive and often demanding timelines successfully. • 5 – 7 years of overall experience IT experience • 3 to 4 years of experience in Data transformations and ETL using Azure technologies • 2 to 3 years of working knowledge on building real-time data pipelines using Apache Spark or Kafka, ETL tools , Azure Data factory, ARM templates • Knowledge of Azure IOT framework and Data Streaming • Excellent understanding of relational and non-relational databases modelling • Proficiency in manipulating and combining large datasets from multiple sources • Excellent knowledge of scripting in Python and Dash or R • Experience with NoSQL databases, such as MongoDB, CosmosDB • Experience visualizing/presenting data using BI tools e.g. PowerBI, Tableau, Plotly, D3.js, Datawrapper, etc. • Knowledge of docker and devops pipeline • Degree in Mathematics/ Computer Science

Signals

Skill data-engineer
0.38
Alias data-engineer
1.00
KRA data-engineer
0.66

Post-classification

Centroidupdated · n=100
Alias collision log
New-role queue
New skills captured9
New KRA captured

Captured for admin review

Data Factory primary Data Engineer pending
ETL primary Data Engineer pending
ARM templates primary Data Engineer pending
Azure IoT primary Data Engineer pending
Data Streaming primary Data Engineer pending
Dash Data Engineer pending
Plotly Data Engineer pending
D3.js Data Engineer pending
Datawrapper Data Engineer pending
Status: completed Created: 2026-05-27T13:57:40.494637Z Updated: 2026-05-27T14:00:14.540122Z API 3 duration: 54327 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

CASE A

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

Exact alias hit on data-engineer (1.0) — no other alias at this confidence; skill_top data-engineer 0.38 does not contradict

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
0
Skipped

Job description

ERM is seeking a Azure Data Engineer / BI Specialist who can support our data analytics services. The ideal candidate must be adept in acquiring real-time data and apply analytical methods on large datasets using a variety of data tools on Azure to discover information that can result in business process optimization or enhancements, or lead to actionable business decisions. Your primary focus will be in developing Data extraction routines and applying data mining techniques, doing statistical analysis, and building high quality prediction models that can be integrated with our analytics solutions. Knowledge of Machine learning algorithms will be beneficial.

Responsibilities:

• Building data pipelines and applying data transformations for batch and real-time messaging systems.
• Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
• Ability to work on various aspects of Data transformations and Data Modelling.
• Enhancing data collection procedures to include information that is relevant for building analytic systems.
• Following and documenting best practices and processes.
• Demonstrating the ability to handle multiple assignments in parallel.
• Meeting aggressive and often demanding timelines successfully.


The job will require working closely with subject matter experts and technical leaders from ERM’s other Business Units, across time zones, as part of diverse teams that may be established for revenue delivery on project to project basis.

Requirements:

• 5 – 7 years of overall experience IT experience
• 3 to 4 years of experience in Data transformations and ETL using Azure technologies
• 2 to 3 years of working knowledge on building real-time data pipelines using Apache Spark or Kafka, ETL tools , Azure Data factory, ARM templates
• Knowledge of Azure IOT framework and Data Streaming
• Excellent understanding of relational and non-relational databases modelling
• Proficiency in manipulating and combining large datasets from multiple sources
• Excellent knowledge of scripting in Python and Dash or R
• Experience with NoSQL databases, such as MongoDB, CosmosDB
• Experience visualizing/presenting data using BI tools e.g. PowerBI, Tableau, Plotly, D3.js, Datawrapper, etc.
• Knowledge of docker and devops pipeline
• Degree in Mathematics/ Computer Science


Who We Are:

As the world’s leading sustainability consulting firm, ERM is uniquely positioned to contribute to the environment and society through the expertise and energy of our employees worldwide. Sustainability is what we do, and is at the heart of both our service offerings and how we operate our business. ERM and our partners are driven by a dynamic vision: By 2021 we will be the clear leader in our chosen markets, we will double in value and we will deliver on our promises to our clients, our people and our investors. For our people, our vision means attracting, inspiring, developing and rewarding our people to work with the best clients and on the biggest challenges, thus creating valuable careers. We achieve our vision in a sustainable manner by maintaining and living our ERM values that include Accountability, Caring for our People, Client Focus, Collaboration, Empowerment, and Transparency.

Please submit your resume and brief cover letter.

ERM does not accept recruiting agency resumes. Please do not forward resumes to our jobs alias, ERM employees or any other company location. ERM is not responsible for any fees related to unsolicited resumes.

ERM is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, marital status or disability status.

Thank you for your interest in ERM!

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 Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure id=188 · azure

Aliases — catalog

  • Azure (CANONICAL) primary

Context tags (catalog)

AKS ARM templates App Service Azure AD Azure Active Directory Azure App Service Azure Blob Azure Blob Storage Azure Cognitive Services Azure Cosmos DB Azure DevOps Azure DevTest Labs Azure Functions Azure Kubernetes Service Azure Logic Apps Azure Monitor Azure Networking Azure Resource Manager Azure SQL Azure SQL Database Azure Security Center Azure Storage Azure Storage Explorer Azure Virtual Machines Bicep Blob Storage Cloud Services Cosmos DB Entra ID Functions Infrastructure as Code Key Vault Log Analytics Logic Apps Resource Groups Serverless Computing Service Bus Storage Account Terraform Virtual Machines

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Cloud Platform
Vendor
Microsoft
License
proprietary
Year introduced
2010
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Azure is broadly adopted and frequently appears in cloud/platform job descriptions alongside AWS and GCP; Microsoft’s ongoing enterprise investment and Azure certification demand signal strong hiring-pipeline relevance.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
46
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 & Managed Services Catalog dimension db id 221

    Library dimension (catalog)

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

  • Cloud Platforms for AI Deployment Catalog dimension db id 211

    Library dimension (catalog)

    Roles linked in library: AI Engineer

  • Cloud Provider Platforms Catalog dimension db id 131

    Library dimension (catalog)

    Roles linked in library: Cloud Architect, Cloud Security Engineer

  • Cloud Security Posture Tools Catalog dimension db id 64

    Library dimension (catalog)

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

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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
Data Engineering Tools
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Apache Spark 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
Existing dimension (library) · Role↔dimension saved
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
ETL 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
Data Engineering Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
ARM templates 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
Infrastructure Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure IoT 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
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Streaming 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
Data Engineering Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
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

  • 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 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)
R Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: R id=194 · r

Aliases — catalog

  • R (VERSION)
  • R 3 (VERSION)
  • R 3.x (VERSION)
  • R 4 (VERSION)
  • R 4.0 (VERSION)
  • R 4.1 (VERSION)
  • R 4.2 (VERSION)
  • R 4.3 (VERSION)
  • R 4.4 (VERSION)
  • R 4.x (VERSION)

Context tags (catalog)

Bioconductor CRAN R Markdown Shiny Tidyverse caret data.table dplyr ggplot2 glm lme4 lubridate rstan tidyr tidyverse

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
R Core Team
License
gpl_v2
Year introduced
1993
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
R 4.x

Maturity reasoning: R appears in many data science, statistics, and analytics job postings, and CRAN remains active with broad package usage across academia and industry.

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)

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Dash 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
Web Frameworks
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
MongoDB Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: MongoDB id=91 · mongodb

Aliases — catalog

  • MongoDB (CANONICAL) primary
  • MongoDB 2.0 (VERSION)
  • MongoDB 2.2 (VERSION)
  • MongoDB 2.4 (VERSION)
  • MongoDB 2.6 (VERSION)
  • MongoDB 3.0 (VERSION)
  • MongoDB 3.2 (VERSION)
  • MongoDB 3.4 (VERSION)
  • MongoDB 3.6 (VERSION)
  • MongoDB 4 (VERSION)
  • MongoDB 4.0 (VERSION)
  • MongoDB 4.2 (VERSION)
  • MongoDB 4.4 (VERSION)
  • MongoDB 5 (VERSION)
  • MongoDB 5.0 (VERSION)
  • MongoDB 6 (VERSION)
  • MongoDB 6.0 (VERSION)
  • MongoDB 7 (VERSION)
  • MongoDB 7.0 (VERSION)
  • MongoDB 8 (VERSION)
  • MongoDB 8.0 (VERSION)

Context tags (catalog)

BSON CRUD GridFS MongoDB Atlas Mongoose NoSQL TTL index aggregation pipeline change streams collections documents indexes replica set sharding

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Document Database
Vendor
MongoDB, Inc.
License
other_open
Year introduced
2009
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
8.0

Maturity reasoning: MongoDB appears in many job descriptions across backend/data roles and is a standard document database in modern stacks; strong GitHub/community activity and broad cloud vendor support indicate mainstream adoption.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
3
Sub-category id
27
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • NoSQL Databases Catalog dimension db id 19

    Library dimension (catalog)

    Roles linked in library: Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
NoSQL Databases
nosql-databases
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cosmos DB Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Cosmos DB id=515 · cosmos-db

Aliases — catalog

  • Cosmos DB (CANONICAL)

Context tags (catalog)

Azure Cassandra API Core (SQL) API Gremlin API MongoDB API NoSQL RU/s TTL Table API change feed consistency levels global distribution multi-region writes partition key throughput

Stored enrichment (catalog DB)

Category
Service
Sub-category
Managed Nosql Database Service
Vendor
Microsoft
License
proprietary
Year introduced
2010
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: Frequently appears in Azure/cloud data engineer JDs and Microsoft positions; strong vendor support and active docs indicate broad adoption rather than niche use.

Skill profile (library / DB)

Skill nature
CLOUD_SERVICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
11
Sub-category id
55
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • NoSQL Databases Catalog dimension db id 19

    Library dimension (catalog)

    Roles linked in library: Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
NoSQL Databases
nosql-databases
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Power BI Primary 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
Tableau Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Tableau id=150 · tableau

Aliases — catalog

  • Tableau (CANONICAL) primary

Context tags (catalog)

LOD expressions Tableau Cloud Tableau Desktop Tableau Prep Tableau Server actions calculated fields dashboards data blending data visualization extracts filters parameters published data sources workbooks

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Bi Analytics Platform
Vendor
Tableau Software
License
proprietary
Year introduced
2003
Confidence
0.96
Version strategy
NOT_APPLICABLE

Maturity reasoning: Tableau appears frequently in BI/data analyst job descriptions and remains a standard enterprise analytics platform 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
Plotly 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
Data Visualization Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
D3.js 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
Data Visualization Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Datawrapper 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
Data Visualization Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
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)
DevOps Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: DevOps id=1216 · devops

Aliases — catalog

  • DevOps (CANONICAL)

Context tags (catalog)

Agile Ansible Automation CI/CD Cloud-native Continuous Deployment Continuous Integration Docker GitOps Infrastructure as Code Jenkins Kubernetes Microservices Monitoring SRE Terraform

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Devops Methodology
Confidence
0.97
Version strategy
NOT_APPLICABLE

Maturity reasoning: DevOps appears in a large share of software and platform engineering job descriptions, often alongside CI/CD, Kubernetes, and cloud tooling; it is a standard hiring-pipeline keyword rather than a niche specialty.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
922
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

  • Deployment and Release Patterns Catalog dimension db id 140

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

  • 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
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Deployment and Release Patterns
deployment-and-release-patterns
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)

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 in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Azure in_db
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure in_db
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure in_db
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure in_db
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Apache Spark in_db
ETL and ELT Tooling
etl-and-elt-tooling
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
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 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)
R in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
MongoDB in_db
NoSQL Databases
nosql-databases
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cosmos DB in_db
NoSQL Databases
nosql-databases
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
Tableau in_db
BI and Visualization Tools
bi-and-visualization-tools
Existing dimension (library) · Role↔dimension saved
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)
DevOps in_db
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
DevOps in_db
Deployment and Release Patterns
deployment-and-release-patterns
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
DevOps in_db
Infrastructure as Code
infrastructure-as-code
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Data Factory | type=Data Engineering Tools subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed ETL | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed ARM templates | type=Infrastructure Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Azure IoT | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Data Streaming | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Dash | type=Web Frameworks subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Plotly | type=Data Visualization Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed D3.js | type=Data Visualization Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Datawrapper | type=Data Visualization Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
nano JD Parser — gpt-4.1-nano click to toggle
RoleAzure Data Engineer / BI Specialist
CompanyERM
Experience5 – 7 years of overall experience IT experience
DomainOther
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": {
    "source_marker": {
      "first_5_words": "As the world\u2019s leading sustainability",
      "last_5_words": "Caring for our People, Client Focus, Collaboration, Empowerment, and Transparency."
    },
    "text": "As the world\u2019s leading sustainability consulting firm, ERM is uniquely positioned to contribute to the environment and society through the expertise and energy of our employees worldwide. Sustainability is what we do, and is at the heart of both our service offerings and how we operate our business. ERM and our partners are driven by a dynamic vision: By 2021 we will be the clear leader in our chosen markets, we will double in value and we will deliver on our promises to our clients, our people and our investors. For our people, our vision means attracting, inspiring, developing and rewarding our people to work with the best clients and on the biggest challenges, thus creating valuable careers. We achieve our vision in a sustainable manner by maintaining and living our ERM values that include Accountability, Caring for our People, Client Focus, Collaboration, Empowerment, and Transparency.",
    "word_count": 130
  },
  "certifications": [],
  "company_name": "ERM",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "Other"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "Bachelor\u0027s - Mathematics / Computer Science",
      "raw": "Degree in Mathematics/ Computer Science",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": 7,
    "min": 5,
    "raw": "5 \u2013 7 years of overall experience IT experience"
  },
  "job_locations": [],
  "role": "Azure Data Engineer / BI Specialist",
  "role_aliases": [
    "Data Engineer",
    "BI Specialist",
    "Azure Data Engineer"
  ],
  "role_archetype": "Data",
  "roles_and_responsibilities": [
    {
      "bullet_count": 7,
      "heading": "Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Building data pipelines and",
        "last_5_words": "aggressive and often demanding timelines successfully."
      },
      "text": "\u2022 Building data pipelines and applying data transformations for batch and real-time messaging systems.\n\u2022 Assessing the effectiveness and accuracy of new data sources and data gathering techniques.\n\u2022 Ability to work on various aspects of Data transformations and Data Modelling.\n\u2022 Enhancing data collection procedures to include information that is relevant for building analytic systems.\n\u2022 Following and documenting best practices and processes.\n\u2022 Demonstrating the ability to handle multiple assignments in parallel.\n\u2022 Meeting aggressive and often demanding timelines successfully.",
      "word_count": 83
    },
    {
      "bullet_count": 11,
      "heading": "Requirements",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 5 \u2013 7 years of overall",
        "last_5_words": "Degree in Mathematics/ Computer Science"
      },
      "text": "\u2022 5 \u2013 7 years of overall experience IT experience\n\u2022 3 to 4 years of experience in Data transformations and ETL using Azure technologies\n\u2022 2 to 3 years of working knowledge on building real-time data pipelines using Apache Spark or Kafka, ETL tools , Azure Data factory, ARM templates\n\u2022 Knowledge of Azure IOT framework and Data Streaming\n\u2022 Excellent understanding of relational and non-relational databases modelling\n\u2022 Proficiency in manipulating and combining large datasets from multiple sources\n\u2022 Excellent knowledge of scripting in Python and Dash or R\n\u2022 Experience with NoSQL databases, such as MongoDB, CosmosDB\n\u2022 Experience visualizing/presenting data using BI tools e.g. PowerBI, Tableau, Plotly, D3.js, Datawrapper, etc.\n\u2022 Knowledge of docker and devops pipeline\n\u2022 Degree in Mathematics/ Computer Science",
      "word_count": 134
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Azure"
    },
    {
      "is_primary": true,
      "skill_name": "Data Factory"
    },
    {
      "is_primary": true,
      "skill_name": "Apache Spark"
    },
    {
      "is_primary": true,
      "skill_name": "Kafka"
    },
    {
      "is_primary": true,
      "skill_name": "ETL"
    },
    {
      "is_primary": true,
      "skill_name": "ARM templates"
    },
    {
      "is_primary": true,
      "skill_name": "Azure IoT"
    },
    {
      "is_primary": true,
      "skill_name": "Data Streaming"
    },
    {
      "is_primary": true,
      "skill_name": "Python"
    },
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      "is_primary": true,
      "skill_name": "R"
    },
    {
      "is_primary": false,
      "skill_name": "Dash"
    },
    {
      "is_primary": true,
      "skill_name": "MongoDB"
    },
    {
      "is_primary": true,
      "skill_name": "Cosmos DB"
    },
    {
      "is_primary": true,
      "skill_name": "Power BI"
    },
    {
      "is_primary": true,
      "skill_name": "Tableau"
    },
    {
      "is_primary": false,
      "skill_name": "Plotly"
    },
    {
      "is_primary": false,
      "skill_name": "D3.js"
    },
    {
      "is_primary": false,
      "skill_name": "Datawrapper"
    },
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  "nano_parsed": {
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        "word_count": 134
      }
    ],
    "urls": []
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "3672c1d8-ab5e-4e9d-90e2-0b01f267ee7e",
  "stage3_signals": {
    "alias_found": true,
    "alias_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 1.0,
        "slug": "data-engineer",
        "total_count": null
      }
    ],
    "kra_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": [
          {
            "kra_text": "Develops batch and real-time streaming data pipelines using Apache Spark, Apache Kafka, Apache Flink, or Airflow for data movement and processing at scale.",
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            "similarity": 0.6654
          },
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            "similarity": 0.6321
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 0.661,
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        "total_count": null
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": [
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          },
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            "kra_text": "Prepares, cleans, and transforms training datasets, manages feature stores, and builds feature engineering pipelines for model training.",
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          },
          {
            "kra_text": "Prepares, cleans, and transforms training datasets, manages feature stores, and builds feature engineering pipelines for model training.",
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          }
        ],
        "matched_count": null,
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        "role_id": 3,
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        "total_count": null
      },
      {
        "display_name": "Java Backend Developer",
        "kra_matches": [
          {
            "kra_text": "persistence and data modeling",
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          },
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            "kra_text": "persistence and data modeling",
            "sentence": "Excellent understanding of relational and non-relational databases modelling",
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          },
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            "kra_text": "persistence and data modeling",
            "sentence": "Enhancing data collection procedures to include information that is relevant for building analytic systems.",
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          }
        ],
        "matched_count": null,
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        "role_id": 79,
        "score": 0.4955,
        "slug": "java-backend-developer",
        "total_count": null
      },
      {
        "display_name": "Node.js Backend Developer",
        "kra_matches": [
          {
            "kra_text": "data modeling and persistence access",
            "sentence": "Excellent understanding of relational and non-relational databases modelling",
            "similarity": 0.4862
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            "sentence": "Ability to work on various aspects of Data transformations and Data Modelling.",
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          },
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            "kra_text": "asynchronous job processing",
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          }
        ],
        "matched_count": null,
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        "role_id": 82,
        "score": 0.4711,
        "slug": "node-backend-developer",
        "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.",
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            "similarity": 0.5022
          },
          {
            "kra_text": "Coordinates model promotion workflows across development, staging, and production environments including integration testing and data contract validation.",
            "sentence": "Ability to work on various aspects of Data transformations and Data Modelling.",
            "similarity": 0.4632
          },
          {
            "kra_text": "Maintains ML platform runbooks, on-call escalation playbooks, and deployment procedure documentation for production operations teams.",
            "sentence": "Following and documenting best practices and processes.",
            "similarity": 0.4457
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 16,
        "score": 0.4704,
        "slug": "ml-ops-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": 6,
        "matched_skills": [
          "Apache Spark",
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        ],
        "role_id": 2,
        "score": 0.375,
        "slug": "data-engineer",
        "total_count": 16
      },
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": 6,
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        ],
        "role_id": 1,
        "score": 0.375,
        "slug": "backend-engineer",
        "total_count": 16
      },
      {
        "display_name": "DevOps Engineer",
        "kra_matches": null,
        "matched_count": 3,
        "matched_skills": [
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        ],
        "role_id": 10,
        "score": 0.1875,
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        "total_count": 16
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": null,
        "matched_count": 3,
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        ],
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        "score": 0.1875,
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        "total_count": 16
      },
      {
        "display_name": "MLOps Engineer",
        "kra_matches": null,
        "matched_count": 3,
        "matched_skills": [
          "Azure",
          "Python",
          "R"
        ],
        "role_id": 16,
        "score": 0.1875,
        "slug": "ml-ops-engineer",
        "total_count": 16
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "A",
    "chosen_role": {
      "display_name": "Data Engineer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 2,
      "score": 1.0,
      "slug": "data-engineer",
      "total_count": null
    },
    "confidence": 1.0,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [],
    "matched_kras": [],
    "matched_skills": [],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.38 does not contradict",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 100,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 6008,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Factory",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 6010,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "ETL",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 6011,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "ARM templates",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 6012,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Azure IoT",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 6013,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Streaming",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 6014,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Dash",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 6015,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Plotly",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 6016,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "D3.js",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 6017,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Datawrapper",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
API 2 — extract-details
{
  "alias_matches": [
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 407,
      "existing_alias_text": "Azure",
      "input_term": "Azure",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "Azure",
        "id": 188,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "azure",
        "sub_category_id": 46,
        "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": 2004,
      "existing_alias_text": "Apache Spark",
      "input_term": "Apache Spark",
      "matched_canonical": {
        "category_id": 5,
        "display_name": "Apache Spark",
        "id": 1350,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "FRAMEWORK",
        "slug": "apache-spark",
        "sub_category_id": 1021,
        "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": 173,
      "existing_alias_text": "Kafka",
      "input_term": "Kafka",
      "matched_canonical": {
        "category_id": 3,
        "display_name": "Kafka",
        "id": 36,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "kafka",
        "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": 67,
      "existing_alias_text": "Python",
      "input_term": "Python",
      "matched_canonical": {
        "category_id": 6,
        "display_name": "Python",
        "id": 5,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "python",
        "sub_category_id": 96,
        "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": 430,
      "existing_alias_text": "R",
      "input_term": "R",
      "matched_canonical": {
        "category_id": 6,
        "display_name": "R",
        "id": 194,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "r",
        "sub_category_id": 96,
        "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": 232,
      "existing_alias_text": "MongoDB",
      "input_term": "MongoDB",
      "matched_canonical": {
        "category_id": 3,
        "display_name": "MongoDB",
        "id": 91,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "mongodb",
        "sub_category_id": 27,
        "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": 863,
      "existing_alias_text": "Cosmos DB",
      "input_term": "Cosmos DB",
      "matched_canonical": {
        "category_id": 11,
        "display_name": "Cosmos DB",
        "id": 515,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CLOUD_SERVICE",
        "slug": "cosmos-db",
        "sub_category_id": 55,
        "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,
        "skill_nature": "PLATFORM",
        "slug": "power-bi",
        "sub_category_id": 111,
        "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": 359,
      "existing_alias_text": "Tableau",
      "input_term": "Tableau",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "Tableau",
        "id": 150,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "tableau",
        "sub_category_id": 111,
        "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": 1852,
      "existing_alias_text": "DevOps",
      "input_term": "DevOps",
      "matched_canonical": {
        "category_id": 8,
        "display_name": "DevOps",
        "id": 1216,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "devops",
        "sub_category_id": 922,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    }
  ],
  "candidate_roles": [
    {
      "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",
      "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"
    },
    {
      "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"
    },
    {
      "display_name": "AI Engineer",
      "id": 13,
      "rationale": null,
      "role_archetype": null,
      "slug": "ai-engineer",
      "source": "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"
    },
    {
      "display_name": "PHP Backend Developer",
      "id": 86,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "php-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Ruby Backend Developer",
      "id": 85,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "ruby-backend-developer",
      "source": "db"
    },
    {
      "display_name": "AR/VR Engineer",
      "id": 8,
      "rationale": null,
      "role_archetype": null,
      "slug": "ar-vr-engineer",
      "source": "db"
    }
  ],
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.38 does not contradict",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "dimensions": [
    {
      "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"
      },
      "input_skill": "Azure",
      "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": "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",
          "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"
        },
        {
          "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"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms \u0026 Managed Services",
        "id": 221,
        "rationale": "Operates and integrates vendor-specific cloud compute, storage, and hosting services.",
        "slug": "cloud-platforms-managed-services",
        "source": "db"
      },
      "input_skill": "Azure",
      "llm_role": null,
      "roles_from_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": "Node.js Backend Developer",
          "id": 82,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Platforms for AI Deployment",
        "id": 211,
        "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
        "slug": "cloud-platforms-for-ai-deployment",
        "source": "db"
      },
      "input_skill": "Azure",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "AI Engineer",
          "id": 13,
          "rationale": null,
          "role_archetype": null,
          "slug": "ai-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Provider Platforms",
        "id": 131,
        "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
        "slug": "cloud-provider-platforms",
        "source": "db"
      },
      "input_skill": "Azure",
      "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": "Cloud Security Posture Tools",
        "id": 64,
        "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
        "slug": "cloud-security-posture-tools",
        "source": "db"
      },
      "input_skill": "Azure",
      "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": "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": "Apache Spark",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
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            "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
            "slug": "ci-cd-pipeline-platforms",
            "source": "db"
          },
          "input_skill": "DevOps",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Deployment and Release Patterns",
            "id": 140,
            "rationale": "Patterns for promoting changes safely across environments, including rollout, rollback, and release gating strategies. Cloud Architects define these patterns so teams can deploy consistently across the platform.",
            "slug": "deployment-and-release-patterns",
            "source": "db"
          },
          "input_skill": "DevOps",
          "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": "Infrastructure as Code",
            "id": 132,
            "rationale": "Declarative provisioning and environment definition tools used to codify cloud infrastructure, repeatable environments, and platform standards. Cloud Architects use these to express reference architectures and guardrails.",
            "slug": "infrastructure-as-code",
            "source": "db"
          },
          "input_skill": "DevOps",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Architect",
              "id": 9,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-architect",
              "source": "db"
            },
            {
              "display_name": "DevOps Engineer",
              "id": 10,
              "rationale": null,
              "role_archetype": null,
              "slug": "devops-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "DevOps",
      "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": [
    "Data Factory",
    "ETL",
    "ARM templates",
    "Azure IoT",
    "Data Streaming",
    "Dash",
    "Plotly",
    "D3.js",
    "Datawrapper"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.38 does not contradict",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Azure",
      "tag": "in_db"
    },
    {
      "skill": "Data Factory",
      "tag": "new"
    },
    {
      "skill": "Apache Spark",
      "tag": "in_db"
    },
    {
      "skill": "Kafka",
      "tag": "in_db"
    },
    {
      "skill": "ETL",
      "tag": "new"
    },
    {
      "skill": "ARM templates",
      "tag": "new"
    },
    {
      "skill": "Azure IoT",
      "tag": "new"
    },
    {
      "skill": "Data Streaming",
      "tag": "new"
    },
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "R",
      "tag": "in_db"
    },
    {
      "skill": "Dash",
      "tag": "new"
    },
    {
      "skill": "MongoDB",
      "tag": "in_db"
    },
    {
      "skill": "Cosmos DB",
      "tag": "in_db"
    },
    {
      "skill": "Power BI",
      "tag": "in_db"
    },
    {
      "skill": "Tableau",
      "tag": "in_db"
    },
    {
      "skill": "Plotly",
      "tag": "new"
    },
    {
      "skill": "D3.js",
      "tag": "new"
    },
    {
      "skill": "Datawrapper",
      "tag": "new"
    },
    {
      "skill": "Docker",
      "tag": "in_db"
    },
    {
      "skill": "DevOps",
      "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 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",
        "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",
            "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",
            "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"
          },
          {
            "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": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms \u0026 Managed Services",
          "id": 221,
          "rationale": "Operates and integrates vendor-specific cloud compute, storage, and hosting services.",
          "slug": "cloud-platforms-managed-services",
          "source": "db"
        },
        "dimension_id": 221,
        "input_skill": "Azure",
        "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": "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": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Platforms for AI Deployment",
          "id": 211,
          "rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
          "slug": "cloud-platforms-for-ai-deployment",
          "source": "db"
        },
        "dimension_id": 211,
        "input_skill": "Azure",
        "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": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Provider Platforms",
          "id": 131,
          "rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
          "slug": "cloud-provider-platforms",
          "source": "db"
        },
        "dimension_id": 131,
        "input_skill": "Azure",
        "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": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud Security Posture Tools",
          "id": 64,
          "rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
          "slug": "cloud-security-posture-tools",
          "source": "db"
        },
        "dimension_id": 64,
        "input_skill": "Azure",
        "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": 188,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "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": "Apache Spark",
        "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": 1350,
        "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": "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"
          }
        ],
        "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,
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        "roles_from_db": [
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        "roles_from_db": [
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          "source": "db"
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        "roles_from_db": [
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        "roles_from_db": [
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        },
        "dimension_id": 152,
        "input_skill": "Docker",
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        "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",
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        ],
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          "source": "db"
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        "roles_from_db": [
          {
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          {
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        ],
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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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