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Pipeline run

6b2c6d2f-fe99-4e62-9f9c-243fe26825e7

Pipeline LLM cost (USD)
API 1: $0.0055 API 2: $0.0007 API 3: $0.0000 Total: $0.0062

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 · Pipeline operations and incident response
Build and operate Azure cloud data/API platform features with application teams: prioritize new ingestion and monitoring requests, manage support queues and sprint backlog, and develop scalable, monitored infrastructure and CI/CD/IaC components.
"Managing respective support queues (e.g. Ingest, Prepare, Storage and Consume, etc.)"
Tech stack maturity
Mainstream Modern
The skill set centers on cloud platforms, serverless functions, CI/CD, microservices, and managed data services, which aligns with a mainstream modern engineering stack rather than bleeding-edge or legacy environments.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
1.70 / 5
· Title match
Has AI skill
AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3): AI
Evidence — skills matched in JD (39)
Python Node.js Azure Functions Cosmos DB Azure Event Hubs Azure Data Lake Storage Azure Storage Queues Agile Scrum Application Lifecycle Management Cloud Computing AWS Azure Microservices Streaming Technologies API ingestion File ingestion Batch transformation Metadata management Monitoring Pub/Sub RDBMS Real-time transformation Octopus Deploy Azure DevOps +14
Skill cluster (8 dimension groups, role-scoped)
Cloud Platforms
AWS Azure
Batch Ingestion and Replication
File ingestion
C# and .NET Languages
C#
Cloud Platforms & Managed Services
Azure Functions
Data Lineage and Metadata
Metadata management
JavaScript and TypeScript
Node.js
Programming Languages for Data Work
Python
Cross-cutting / unaligned
Cosmos DB Azure Event Hubs Azure Data Lake Storage Azure Storage Queues Agile Scrum Application Lifecycle Management Cloud Computing Microservices Streaming Technologies API ingestion Batch transformation Monitoring Pub/Sub RDBMS Real-time transformation Octopus Deploy Azure DevOps APIM Azure Monitor Azure Table Storage Azure Databricks Azure SQL Database Azure AI Search Azure SignalR Infrastructure as Code CI/CD Incident Management Network Security Sprint Planning
Show KRA description ↓
Working with the application teams to prioritize new requests for functionality. Specifically, new user-facing functionality (e.g., the ability to ingest IoT data, subscription-based consumption, etc.)Addressing internal functionality (e.g., monitoring and alerting based on application performance, automated testing frameworks, etc.)Managing respective support queues (e.g., Ingest, Prepare, Storage and Consume, etc.) Note: agreed upon SLAs will be established post burn-in periodManage backlog via effective sprint planning based on feedback from the application teamsParticipating in monthly architecture review boardMentoring and coaching the application teams on tools, technology and design patternsEnsuring that the production environment is well built and that there is a clear escalation path for production issuesEnsuring solution architecture meets JLL's requirements including, but not limited to, those regarding cloud spend, scalability, performance, etc.Developing the framework components for JLL's cloud environmentDeveloping infrastructure that is scalable, reliable, and monitoredBuilding a relationship with Cloud providers, in order to take advantage of their most appropriate technology offeringsCollaborating with the application team leads to ensure that the application teams' needs are met through the CI/CD framework, component monitoring and stats, incident escalationInculcating "infrastructure as code" mentality in the Platform \ team overallUtilizing Agile practices to manage and deliver features.Create and maintain incident management requests to product group/engineering group.Compare solution alternatives across both technical and business parameters which support the define cost and service requirements. Bachelor’s degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science. Minimum of 3 years of experience as a data and API developer using Python/Nodejs, Azure Functions, Cosmos DB, Azure Event Hubs, Azure Data Lake Storage, Azure Storage Queues etc.Project experience leveraging Agile with SCRUM, and Application Lifecycle Management (ALM). Excellent technical, analytical and organizational skills.Cloud data engineer who is an expert in technology, should be able to quickly adopt to change and one who understands the technologies supporting areas such as Cloud Computing (AWS, Azure, etc.), Micro Services, Streaming Technologies, Network, Security etc.,Minimum of 3-5 years of experience with, API ingestion, file ingestion, batch transformation, metadata management, monitoring, pub/sub consumption, RDBMS ingestion and real-time transformation.Minimum of 3-5 years using the following technology or equivalent: Octopus, Azure DevOps, Azure functions, Python, C#, APIM, Azure Event Hub, Azure Data Lake Storage (Gen 2), Azure Monitor, Azure Table Storage, Azure Databricks, Azure SQL Database, Azure Search, Azure Cosmo Data Store, and Azure SignalR.

Signals

Skill backend-engineer
0.19
Alias data-engineer
1.00
KRA cloud-architect
0.49

Post-classification

Centroidupdated · n=503
Alias collision log
New-role queue
New skills captured21
New KRA captured

Captured for admin review

Azure Event Hubs primary Data Engineer pending
Azure Data Lake Storage primary Data Engineer pending
Azure Storage Queues primary Data Engineer pending
Application Lifecycle Management primary Data Engineer pending
Cloud Computing primary Data Engineer pending
Streaming Technologies primary Data Engineer pending
Network Data Engineer pending
Security Data Engineer pending
API ingestion primary Data Engineer pending
Batch transformation primary Data Engineer pending
Real-time transformation primary Data Engineer pending
Octopus Deploy primary Data Engineer pending
APIM primary Data Engineer pending
Azure Monitor primary Data Engineer pending
Azure Table Storage primary Data Engineer pending
Azure Databricks primary Data Engineer pending
Azure SQL Database primary Data Engineer pending
Azure AI Search primary Data Engineer pending
Azure SignalR primary Data Engineer pending
Infrastructure as Code primary Data Engineer pending
Incident Management primary Data Engineer pending
Status: completed Created: 2026-05-27T17:19:06.227822Z Updated: 2026-05-27T17:21:07.489454Z API 3 duration: 31000 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 backend-engineer 0.19 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
5
Skipped

Job description

Senior Cloud Data Engineer

Unified Data Platform

JLL/Technologies Centre of Expertise (JLLT CoE) (Bangalore)

What this job involves:

About The Role

#JLLTechAmbitions
We are looking for a senior cloud data engineer who is a self-starter to work in a diverse and fast-paced environment to support, maintain and advance the capabilities of the unified data platform.This is an individual contributor role that is responsible for designing, developing and supporting solutions that are strategic for the business and built on the latest technologies and patterns.This a global role that requires partnering with the broader JLLT team at the country, regional and global level by utilizing in-depth knowledge of Azure, infrastructure, technologies and dev/ops engineering experience.

Responsibilities
Working with the application teams to prioritize new requests for functionality. Specifically, new user-facing functionality (e.g., the ability to ingest IoT data, subscription-based consumption, etc.)Addressing internal functionality (e.g., monitoring and alerting based on application performance, automated testing frameworks, etc.)Managing respective support queues (e.g., Ingest, Prepare, Storage and Consume, etc.) Note: agreed upon SLAs will be established post burn-in periodManage backlog via effective sprint planning based on feedback from the application teamsParticipating in monthly architecture review boardMentoring and coaching the application teams on tools, technology and design patternsEnsuring that the production environment is well built and that there is a clear escalation path for production issuesEnsuring solution architecture meets JLL's requirements including, but not limited to, those regarding cloud spend, scalability, performance, etc.Developing the framework components for JLL's cloud environmentDeveloping infrastructure that is scalable, reliable, and monitoredBuilding a relationship with Cloud providers, in order to take advantage of their most appropriate technology offeringsCollaborating with the application team leads to ensure that the application teams' needs are met through the CI/CD framework, component monitoring and stats, incident escalationInculcating "infrastructure as code" mentality in the Platform \ team overallUtilizing Agile practices to manage and deliver features.Create and maintain incident management requests to product group/engineering group.Compare solution alternatives across both technical and business parameters which support the define cost and service requirements.

Sounds like you? To apply you need to be:

Experience & Education
Bachelor’s degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science. Minimum of 3 years of experience as a data and API developer using Python/Nodejs, Azure Functions, Cosmos DB, Azure Event Hubs, Azure Data Lake Storage, Azure Storage Queues etc.Project experience leveraging Agile with SCRUM, and Application Lifecycle Management (ALM).

Technical Skills & Competencies
Excellent technical, analytical and organizational skills.Cloud data engineer who is an expert in technology, should be able to quickly adopt to change and one who understands the technologies supporting areas such as Cloud Computing (AWS, Azure, etc.), Micro Services, Streaming Technologies, Network, Security etc.,Minimum of 3-5 years of experience with, API ingestion, file ingestion, batch transformation, metadata management, monitoring, pub/sub consumption, RDBMS ingestion and real-time transformation.Minimum of 3-5 years using the following technology or equivalent: Octopus, Azure DevOps, Azure functions, Python, C#, APIM, Azure Event Hub, Azure Data Lake Storage (Gen 2), Azure Monitor, Azure Table Storage, Azure Databricks, Azure SQL Database, Azure Search, Azure Cosmo Data Store, and Azure SignalR.

What we can do for you:

You’ll join an entrepreneurial, inclusive culture. One where we succeed together – across the desk and around the globe. Where like-minded people work naturally together to achieve great things.

Our Total Rewards program reflects our commitment to helping you achieve your ambitions in career, recognition, well-being, benefits and pay.

Join us to develop your strengths and enjoy a fulfilling career full of varied experiences. Keep those ambitions in sights and imagine where JLL can take you...

Apply today!

JLL Privacy Notice

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Jones Lang LaSalle (“JLL”) is an Equal Opportunity Employer and is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process – including the online application and/or overall selection process – you may email us at AccomodationRequest@am.jll.com. This email is only to request an accommodation. Please direct any other general recruiting inquiries to our Contact Us page > I want to work for JLL.

Skills from this JD

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

Python Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Python id=5 · python

Aliases — catalog

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

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

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

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

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

  • Programming Languages & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • Programming Languages and Scripting Catalog dimension db id 59

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • Programming Languages for XR Catalog dimension db id 97

    Library dimension (catalog)

    Roles linked in library: AR/VR Engineer

  • Python Programming Catalog dimension db id 290

    Library dimension (catalog)

    Roles linked in library: Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Node.js Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Node.js id=1564 · node-js

Aliases — catalog

  • Node.js (CANONICAL) primary
  • Node 20 LTS (VERSION)
  • Node 20.x (VERSION)
  • Node.js 20 (VERSION)
  • Node.js 20 LTS (VERSION)
  • Node.js 20.x (VERSION)
  • node (VERSION)
  • node 10 (VERSION)
  • node 12 (VERSION)
  • node 14 (VERSION)
  • node 16 (VERSION)
  • node 18 (VERSION)
  • node 20 (VERSION)
  • node v10 (VERSION)
  • node v12 (VERSION)
  • node v14 (VERSION)
  • node v16 (VERSION)
  • node v18 (VERSION)
  • node v20 (VERSION)
  • node.js (VERSION)
  • node.js 10 (VERSION)
  • node.js 12 (VERSION)
  • node.js 14 (VERSION)
  • node.js 16 (VERSION)
  • node.js 18 (VERSION)
  • node.js 20 (VERSION)
  • nodejs (VERSION)
  • nodejs 10 (VERSION)
  • nodejs 12 (VERSION)
  • nodejs 14 (VERSION)
  • nodejs 16 (VERSION)
  • nodejs 18 (VERSION)
  • nodejs 20 (VERSION)

Context tags (catalog)

API Asynchronous Event-driven Express GraphQL JavaScript Jest Koa Microservices Middleware Mocha MongoDB Mongoose NestJS RESTful Socket.io TypeScript npm

Stored enrichment (catalog DB)

Category
Runtime
Sub-category
Javascript Runtime
Vendor
OpenJS Foundation
License
mit
Year introduced
2009
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
20

Maturity reasoning: Node.js appears in high-volume job postings across backend/full-stack roles and is a standard runtime in major cloud/vendor docs and ecosystem tooling, indicating broad hiring-pipeline adoption.

Skill profile (library / DB)

Skill nature
RUNTIME
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
67
Sub-category id
1872
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • JavaScript and TypeScript Catalog dimension db id 114

    Library dimension (catalog)

    Roles linked in library: Angular Frontend Developer, Frontend Developer, Ionic Developer, Node.js Backend Developer, React Frontend Developer, React Native Developer, Svelte Frontend Developer, Vue Frontend Developer, Web Developer

  • Web Application Frameworks Catalog dimension db id 2

    Library dimension (catalog)

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

API 3 link attempts (this skill)

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

Aliases — catalog

  • Azure Functions (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Cloud Platforms & Hosting Providers Catalog dimension db id 278

    Library dimension (catalog)

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

  • Cloud Platforms & Managed Services Catalog dimension db id 221

    Library dimension (catalog)

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

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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)
Azure Event Hubs Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

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

Aliases — catalog

  • Azure Blob Storage (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Cloud Storage and Data Services Catalog dimension db id 144

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

  • Cloud Storage and File Formats Catalog dimension db id 35

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Storage and Data Services
cloud-storage-and-data-services
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Cloud Storage and File Formats
cloud-storage-and-file-formats
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Azure Storage Queues 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
Message Brokers
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Agile Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Agile id=520 · agile

Aliases — catalog

  • Agile (CANONICAL) primary

Context tags (catalog)

Kanban SAFe Scrum backlog backlog grooming burndown burndown chart continuous delivery continuous improvement cross-functional daily standup epics incremental development iteration iteration planning lean product backlog product owner retrospective sprint sprint planning stand-up story points user stories velocity

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Agile
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Agile appears in a large share of software job descriptions and is a standard hiring-pipeline requirement; Scrum/Kanban are commonly listed alongside it, showing broad market adoption.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
3594
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Software Concepts, Patterns & Practices Catalog dimension db id 478

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Scrum Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Scrum id=1215 · scrum

Aliases — catalog

  • Scrum (CANONICAL) primary

Context tags (catalog)

Agile Kanban backlog burndown chart cross-functional team daily standup definition of done increment product owner release planning retrospective scrum framework scrum master sprint story points user stories velocity

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Scrum
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Scrum appears in a large share of agile project-management and product-owner job descriptions, and Scrum Alliance/PSM certifications are widely requested in hiring pipelines.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
3627
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Software Concepts, Patterns & Practices Catalog dimension db id 478

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Application Lifecycle Management 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
Practices
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Cloud Computing 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
AWS Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: AWS id=187 · aws

Aliases — catalog

  • AWS (CANONICAL) primary

Context tags (catalog)

API Gateway AWS CLI Auto Scaling CloudFormation CloudFront CloudTrail CloudWatch Cognito DynamoDB EC2 ECS EKS Elastic Beanstalk Elastic Load Balancing IAM KMS Lambda RDS Route 53 S3 SNS SQS Serverless VPC

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Cloud Platform
Vendor
Amazon
License
other_open
Year introduced
2006
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: AWS is a hiring-pipeline staple: it appears in a large share of cloud/DevOps job descriptions and dominates public cloud market share, with broad certification and vendor ecosystem support.

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 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

  • Vendor Product Families Catalog dimension db id 477

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
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)
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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

  • Vendor Product Families Catalog dimension db id 477

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

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)
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Microservices Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: microservices id=41 · microservices

Aliases — catalog

  • microservices (CANONICAL) primary

Context tags (catalog)

API Gateway API gateway CQRS DevOps Docker Kubernetes REST API RESTful services Saga pattern Spring Boot circuit breaker containerization decentralized distributed tracing domain-driven design event sourcing event-driven event-driven architecture gRPC load balancing message broker microservices patterns monitoring scalability service discovery service mesh

Stored enrichment (catalog DB)

Category
Architecture
Sub-category
Distributed System Architecture
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Microservices is a common architecture in job descriptions across backend/cloud roles, and major vendors like AWS, Google Cloud, and Kubernetes ecosystems provide first-class support and reference patterns.

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Microservices and Distributed Systems Catalog dimension db id 9

    Library dimension (catalog)

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

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Microservices and Distributed Systems
microservices-and-distributed-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Streaming Technologies 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Network 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Security 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
API ingestion 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
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
File ingestion Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: File ingestion id=143 · file-ingestion

Aliases — catalog

  • File ingestion (CANONICAL) primary

Context tags (catalog)

CSV ETL FTP JSON Parquet SFTP batch processing checksum data pipeline deduplication file parsing metadata extraction object storage schema validation streaming

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Data Ingestion Methodology
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common in data/platform JDs for ETL/ELT and document pipelines; vendors like AWS, GCP, and Databricks all market file ingestion features, indicating broad adoption.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
104
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Batch Ingestion and Replication Catalog dimension db id 29

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Batch Ingestion and Replication
batch-ingestion-and-replication
Existing dimension (library) · Role↔dimension saved
Batch transformation 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
Metadata management Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Metadata management id=137 · metadata-management

Aliases — catalog

  • Metadata management (CANONICAL) primary

Context tags (catalog)

business glossary cataloging controlled vocabulary data catalog data classification data dictionary data governance data lineage data quality data stewardship master data management metadata repository ontology schema registry taxonomy

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Metadata Management Methodology
Confidence
0.92
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common in data/platform JDs: roles for data governance, MDM, and cataloging routinely list metadata management alongside tools like Collibra/Alation and cloud data catalogs.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
109
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Data Lineage and Metadata Catalog dimension db id 28

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Data Lineage and Metadata
data-lineage-and-metadata
Existing dimension (library) · Role↔dimension saved
Monitoring Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Monitoring id=1218 · monitoring

Aliases — catalog

  • Monitoring (CANONICAL)

Context tags (catalog)

ELK Stack Grafana Prometheus SLI SLO alerting anomaly detection dashboards health checks incident response logging metrics monitoring as code observability tracing

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Observability Monitoring
Confidence
0.88
Version strategy
NOT_APPLICABLE

Maturity reasoning: Monitoring is a standard requirement in most SRE/DevOps job descriptions and is bundled into major platforms like AWS CloudWatch, Datadog, and Prometheus, indicating broad market adoption.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
924
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Observability and Incident Triage Catalog dimension db id 155

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Observability and Incident Triage
observability-and-incident-triage
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Pub/Sub Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: pub/sub id=2443 · pub-sub

Aliases — catalog

  • pub/sub (CANONICAL) primary

Context tags (catalog)

Kafka RabbitMQ acknowledgment asynchronous de-coupling event sourcing event stream event-driven load balancing message broker message payload message queue message routing microservices producer publish publisher real-time data scalability stream processing subscribe subscriber topic

Stored enrichment (catalog DB)

Category
Architecture
Sub-category
Messaging Architecture
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Pub/sub is broadly used in cloud and event-driven systems; it appears in many JDs for Kafka, SNS/SQS, and GCP Pub/Sub, indicating a staple market skill rather than a niche pattern.

Skill profile (library / DB)

Skill nature
PATTERN
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
1
Sub-category id
3470
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

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)
RDBMS Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: RDBMS id=1355 · rdbms

Aliases — catalog

  • RDBMS (CANONICAL)

Context tags (catalog)

ACID ER diagrams SQL backup and recovery data integrity data modeling database tuning foreign keys indexes joins normalization query optimization schema design stored procedures transactions views

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Relational Database Management System
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: RDBMS is a core requirement in many job descriptions across backend, data, and DBA roles; PostgreSQL, MySQL, and SQL Server remain standard enterprise stacks.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
3
Sub-category id
1023
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Real-time transformation 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
Octopus Deploy 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
DevOps Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure DevOps Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure DevOps id=1214 · azure-devops

Aliases — catalog

  • Azure DevOps (CANONICAL)

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • CI/CD Pipeline Platforms Catalog dimension db id 150

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C# Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: C# id=4 · c

Aliases — catalog

  • C# (CANONICAL) primary
  • C (CANONICAL)
  • C# 1 (VERSION)
  • C# 10 (VERSION)
  • C# 11 (VERSION)
  • C# 12 (VERSION)
  • C# 13 (VERSION)
  • C# 14 (VERSION)
  • C# 2 (VERSION)
  • C# 3 (VERSION)
  • C# 4 (VERSION)
  • C# 5 (VERSION)
  • C# 6 (VERSION)
  • C# 7 (VERSION)
  • C# 8 (VERSION)
  • C# 9 (VERSION)
  • C# latest (VERSION)
  • C#1 (VERSION)
  • C#10 (VERSION)
  • C#11 (VERSION)
  • C#12 (VERSION)
  • C#2 (VERSION)
  • C#3 (VERSION)
  • C#4 (VERSION)
  • C#5 (VERSION)
  • C#6 (VERSION)
  • C#7 (VERSION)
  • C#8 (VERSION)
  • C#9 (VERSION)
  • C++ (CANONICAL)
  • C++03 (VERSION)
  • C++11 (VERSION)
  • C++14 (VERSION)
  • C++17 (VERSION)
  • C++20 (VERSION)
  • C++23 (VERSION)
  • C++26 (VERSION)
  • C++98 (VERSION)
  • c sharp (VERSION)
  • c# (VERSION)
  • cpp03 (VERSION)
  • cpp11 (VERSION)
  • cpp14 (VERSION)
  • cpp17 (VERSION)
  • cpp20 (VERSION)
  • cpp23 (VERSION)
  • cpp26 (VERSION)
  • cpp98 (VERSION)
  • csharp (VERSION)
  • modern C++ (VERSION)

Context tags (catalog)

.NET ASP.NET Azure Boost C# 9 C11 C99 CLR CMake Entity Framework LINQ MSBuild MVC Makefile NuGet Qt RAII Roslyn STL TDD Unity Visual Studio WPF Web API WinForms Xamarin async/await attributes buffer overflow constexpr delegates dependency injection dynamic memory events free function pointer gcc gdb header files inline interfaces linker malloc memory leak memory management move semantics multithreading operator overloading pointer pointers preprocessor segmentation fault smart pointers stdio.h stdlib.h struct syntax error templates typedef xUnit

Stored enrichment (catalog DB)

Category
Language
Sub-category
Programming Language
Vendor
Microsoft
License
mit
Year introduced
2000
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
latest

Maturity reasoning: C# is a mainstream hiring staple with high JD volume across .NET, Azure, and enterprise roles; Microsoft continues active platform investment in .NET, reinforcing broad adoption.

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)

  • C# and .NET Languages Catalog dimension db id 362

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer

  • Cross-Platform App Languages Catalog dimension db id 167

    Library dimension (catalog)

    Roles linked in library: Hybrid Mobile Developer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

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

  • 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

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Sitecore Development Languages Catalog dimension db id 438

    Library dimension (catalog)

    Roles linked in library: Sitecore Dev

  • Video Codec Languages and DSLs Catalog dimension db id 225

    Library dimension (catalog)

    Roles linked in library: Video Codec Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
C# and .NET Languages
c-and-net-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cross-Platform App Languages
cross-platform-app-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 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)
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Sitecore Development Languages
sitecore-development-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Video Codec Languages and DSLs
video-codec-languages-and-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
APIM 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
API Management
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure Monitor 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
Monitoring Tools
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Azure Table Storage Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Azure Blob Storage id=172 · azure-blob-storage

Aliases — catalog

  • Azure Blob Storage (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Cloud Storage and Data Services Catalog dimension db id 144

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

  • Cloud Storage and File Formats Catalog dimension db id 35

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Storage and Data Services
cloud-storage-and-data-services
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Cloud Storage and File Formats
cloud-storage-and-file-formats
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Azure Databricks Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

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

Aliases — catalog

  • Azure Cognitive Search (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • Search and Content Discovery Catalog dimension db id 356

    Library dimension (catalog)

    Roles linked in library: Drupal Dev, Sitecore Dev

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Search and Content Discovery
search-and-content-discovery
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Azure SignalR 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
Infrastructure as Code 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
Practices
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
CI/CD Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: CI/CD id=1190 · ci-cd

Aliases — catalog

  • CI/CD (CANONICAL)

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • CI/CD Pipeline Platforms Catalog dimension db id 150

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

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

    Library dimension (catalog)

    Roles linked in library: ML Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Incident Management 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
Practices
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Sprint Planning Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: sprint planning id=4550 · sprint-planning

Aliases — catalog

  • sprint planning (CANONICAL) primary

Context tags (catalog)

agile framework backlog refinement burndown chart cross-functional team definition of done incremental delivery iteration planning retrospective scrum ceremonies sprint goals stakeholder engagement task estimation timeboxing user stories velocity tracking

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Sprint Planning
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Sprint planning is a standard Scrum ceremony and appears routinely in Agile job descriptions; it’s a hiring-pipeline staple for product and engineering teams.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
3628
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Delivery Planning and Execution Catalog dimension db id 461

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Delivery Planning and Execution
delivery-planning-and-execution
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
Python in_db
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Python in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Node.js in_db
JavaScript and TypeScript
javascript-and-typescript
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Node.js in_db
Web Application Frameworks
web-application-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Functions in_db
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Functions in_db
Cloud Platforms & Managed Services
cloud-platforms-managed-services
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cosmos DB in_db
NoSQL Databases
nosql-databases
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Data Lake Storage new
Cloud Storage and Data Services
cloud-storage-and-data-services
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Azure Data Lake Storage new
Cloud Storage and File Formats
cloud-storage-and-file-formats
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Agile in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile in_db
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Scrum in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Scrum in_db
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
AWS in_db
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Cloud Provider Platforms
cloud-provider-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Cloud Security Posture Tools
cloud-security-posture-tools
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
AWS in_db
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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)
Azure in_db
Vendor Product Families
vendor-product-families
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Microservices in_db
Microservices and Distributed Systems
microservices-and-distributed-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
File ingestion in_db
Batch Ingestion and Replication
batch-ingestion-and-replication
Existing dimension (library) · Role↔dimension saved
Metadata management in_db
Data Lineage and Metadata
data-lineage-and-metadata
Existing dimension (library) · Role↔dimension saved
Monitoring in_db
Observability and Incident Triage
observability-and-incident-triage
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Pub/Sub in_db
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
RDBMS in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure DevOps in_db
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C# in_db
C# and .NET Languages
c-and-net-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C# in_db
Cross-Platform App Languages
cross-platform-app-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C# in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C# in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C# in_db
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C# in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C# in_db
Sitecore Development Languages
sitecore-development-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C# in_db
Video Codec Languages and DSLs
video-codec-languages-and-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Azure Table Storage new
Cloud Storage and Data Services
cloud-storage-and-data-services
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Azure Table Storage new
Cloud Storage and File Formats
cloud-storage-and-file-formats
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Azure AI Search new
Search and Content Discovery
search-and-content-discovery
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
CI/CD in_db
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD in_db
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Sprint Planning in_db
Delivery Planning and Execution
delivery-planning-and-execution
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Azure Event Hubs | type=Cloud Platforms subtype=Message Brokers nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Azure Storage Queues | type=Cloud Platforms subtype=Message Brokers nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Application Lifecycle Management | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Cloud Computing | type=Concepts subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed Streaming Technologies | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Network | type=Concepts subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed Security | type=Concepts subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed API ingestion | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Batch transformation | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Real-time transformation | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Octopus Deploy | type=DevOps Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed APIM | type=Cloud Platforms subtype=API Management nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Azure Monitor | type=Cloud Platforms subtype=Monitoring Tools nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Azure Databricks | type=Cloud Platforms subtype=Machine Learning Frameworks nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Azure SQL Database | type=Cloud Platforms subtype=Databases nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Azure SignalR | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed Infrastructure as Code | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Incident Management | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR
dimension_skill_link_proposed Azure Data Lake Storage ↔ Cloud Storage and Data Services
dimension_skill_link_proposed Azure Data Lake Storage ↔ Cloud Storage and File Formats
role_dimension_link_proposed Data Engineer ↔ Cloud Storage and File Formats
dimension_skill_link_proposed Azure Table Storage ↔ Cloud Storage and Data Services
dimension_skill_link_proposed Azure Table Storage ↔ Cloud Storage and File Formats
role_dimension_link_proposed Data Engineer ↔ Cloud Storage and File Formats
dimension_skill_link_proposed Azure AI Search ↔ Search and Content Discovery
nano JD Parser — gpt-4.1-nano click to toggle
RoleSenior Cloud Data Engineer
CompanyJones Lang LaSalle (JLL)
ExperienceMinimum of 3 years of experience as a data and API developer
DomainIT Services & Consulting
Location Bangalore, India (null)
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": {
    "source_marker": {
      "first_5_words": "Jones Lang LaSalle (JLL), together with",
      "last_5_words": "delete it safely and securely."
    },
    "text": "Jones Lang LaSalle (JLL), together with its subsidiaries and affiliates, is a leading global provider of real estate and investment management services. We take our responsibility to protect the personal information provided to us seriously. Generally the personal information we collect from you are for the purposes of processing in connection with JLL\u2019s recruitment process. We endeavour to keep your personal information secure with appropriate level of security and keep for as long as we need it for legitimate business or legal reasons. We will then delete it safely and securely.",
    "word_count": 64
  },
  "certifications": [],
  "company_name": "Jones Lang LaSalle (JLL)",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [
        "Tech Consulting",
        "Cloud Services"
      ],
      "domain": "IT Services \u0026 Consulting"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "BTECH/BE/BSC - Information Science / Computer Science / Mathematics / Statistics",
      "raw": "Bachelor\u2019s degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science.",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": null,
    "min": 3,
    "raw": "Minimum of 3 years of experience as a data and API developer"
  },
  "job_locations": [
    {
      "aliases": [
        "Bengaluru"
      ],
      "city": "Bangalore",
      "country": "India",
      "state": null,
      "work_mode": "null"
    }
  ],
  "role": "Senior Cloud Data Engineer",
  "role_aliases": [
    "Cloud Data Engineer",
    "Data Engineer",
    "Senior Data Engineer"
  ],
  "role_archetype": "Data",
  "roles_and_responsibilities": [
    {
      "bullet_count": 0,
      "heading": "Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Working with the application teams",
        "last_5_words": "cost and service requirements."
      },
      "text": "Working with the application teams to prioritize new requests for functionality. Specifically, new user-facing functionality (e.g., the ability to ingest IoT data, subscription-based consumption, etc.)Addressing internal functionality (e.g., monitoring and alerting based on application performance, automated testing frameworks, etc.)Managing respective support queues (e.g., Ingest, Prepare, Storage and Consume, etc.) Note: agreed upon SLAs will be established post burn-in periodManage backlog via effective sprint planning based on feedback from the application teamsParticipating in monthly architecture review boardMentoring and coaching the application teams on tools, technology and design patternsEnsuring that the production environment is well built and that there is a clear escalation path for production issuesEnsuring solution architecture meets JLL\u0027s requirements including, but not limited to, those regarding cloud spend, scalability, performance, etc.Developing the framework components for JLL\u0027s cloud environmentDeveloping infrastructure that is scalable, reliable, and monitoredBuilding a relationship with Cloud providers, in order to take advantage of their most appropriate technology offeringsCollaborating with the application team leads to ensure that the application teams\u0027 needs are met through the CI/CD framework, component monitoring and stats, incident escalationInculcating \"infrastructure as code\" mentality in the Platform \\ team overallUtilizing Agile practices to manage and deliver features.Create and maintain incident management requests to product group/engineering group.Compare solution alternatives across both technical and business parameters which support the define cost and service requirements.",
      "word_count": 309
    },
    {
      "bullet_count": 0,
      "heading": "Experience \u0026 Education",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Bachelor\u2019s degree in Information Science",
        "last_5_words": "Agile with SCRUM, and Application"
      },
      "text": "Bachelor\u2019s degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science. Minimum of 3 years of experience as a data and API developer using Python/Nodejs, Azure Functions, Cosmos DB, Azure Event Hubs, Azure Data Lake Storage, Azure Storage Queues etc.Project experience leveraging Agile with SCRUM, and Application Lifecycle Management (ALM).",
      "word_count": 56
    },
    {
      "bullet_count": 0,
      "heading": "Technical Skills \u0026 Competencies",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Excellent technical, analytical and organizational",
        "last_5_words": "Azure SQL Database, Azure Search, Azure"
      },
      "text": "Excellent technical, analytical and organizational skills.Cloud data engineer who is an expert in technology, should be able to quickly adopt to change and one who understands the technologies supporting areas such as Cloud Computing (AWS, Azure, etc.), Micro Services, Streaming Technologies, Network, Security etc.,Minimum of 3-5 years of experience with, API ingestion, file ingestion, batch transformation, metadata management, monitoring, pub/sub consumption, RDBMS ingestion and real-time transformation.Minimum of 3-5 years using the following technology or equivalent: Octopus, Azure DevOps, Azure functions, Python, C#, APIM, Azure Event Hub, Azure Data Lake Storage (Gen 2), Azure Monitor, Azure Table Storage, Azure Databricks, Azure SQL Database, Azure Search, Azure Cosmo Data Store, and Azure SignalR.",
      "word_count": 118
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "Node.js"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Functions"
    },
    {
      "is_primary": true,
      "skill_name": "Cosmos DB"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Event Hubs"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Data Lake Storage"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Storage Queues"
    },
    {
      "is_primary": true,
      "skill_name": "Agile"
    },
    {
      "is_primary": true,
      "skill_name": "Scrum"
    },
    {
      "is_primary": true,
      "skill_name": "Application Lifecycle Management"
    },
    {
      "is_primary": true,
      "skill_name": "Cloud Computing"
    },
    {
      "is_primary": true,
      "skill_name": "AWS"
    },
    {
      "is_primary": true,
      "skill_name": "Azure"
    },
    {
      "is_primary": true,
      "skill_name": "Microservices"
    },
    {
      "is_primary": true,
      "skill_name": "Streaming Technologies"
    },
    {
      "is_primary": false,
      "skill_name": "Network"
    },
    {
      "is_primary": false,
      "skill_name": "Security"
    },
    {
      "is_primary": true,
      "skill_name": "API ingestion"
    },
    {
      "is_primary": true,
      "skill_name": "File ingestion"
    },
    {
      "is_primary": true,
      "skill_name": "Batch transformation"
    },
    {
      "is_primary": true,
      "skill_name": "Metadata management"
    },
    {
      "is_primary": true,
      "skill_name": "Monitoring"
    },
    {
      "is_primary": true,
      "skill_name": "Pub/Sub"
    },
    {
      "is_primary": true,
      "skill_name": "RDBMS"
    },
    {
      "is_primary": true,
      "skill_name": "Real-time transformation"
    },
    {
      "is_primary": true,
      "skill_name": "Octopus Deploy"
    },
    {
      "is_primary": true,
      "skill_name": "Azure DevOps"
    },
    {
      "is_primary": true,
      "skill_name": "C#"
    },
    {
      "is_primary": true,
      "skill_name": "APIM"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Monitor"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Table Storage"
    },
    {
      "is_primary": true,
      "skill_name": "Azure Databricks"
    },
    {
      "is_primary": true,
      "skill_name": "Azure SQL Database"
    },
    {
      "is_primary": true,
      "skill_name": "Azure AI Search"
    },
    {
      "is_primary": true,
      "skill_name": "Azure SignalR"
    },
    {
      "is_primary": true,
      "skill_name": "Infrastructure as Code"
    },
    {
      "is_primary": true,
      "skill_name": "CI/CD"
    },
    {
      "is_primary": true,
      "skill_name": "Incident Management"
    },
    {
      "is_primary": false,
      "skill_name": "Sprint Planning"
    }
  ],
  "jd_role": {
    "display_name": "Senior Cloud Data Engineer",
    "rationale": null,
    "role_aliases": [
      "Cloud Data Engineer",
      "Data Engineer",
      "Senior Data Engineer"
    ],
    "role_archetype": "Data",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": {
      "source_marker": {
        "first_5_words": "Jones Lang LaSalle (JLL), together with",
        "last_5_words": "delete it safely and securely."
      },
      "text": "Jones Lang LaSalle (JLL), together with its subsidiaries and affiliates, is a leading global provider of real estate and investment management services. We take our responsibility to protect the personal information provided to us seriously. Generally the personal information we collect from you are for the purposes of processing in connection with JLL\u2019s recruitment process. We endeavour to keep your personal information secure with appropriate level of security and keep for as long as we need it for legitimate business or legal reasons. We will then delete it safely and securely.",
      "word_count": 64
    },
    "certifications": [],
    "company_name": "Jones Lang LaSalle (JLL)",
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [
          "Tech Consulting",
          "Cloud Services"
        ],
        "domain": "IT Services \u0026 Consulting"
      },
      "secondary": null
    },
    "education": [
      {
        "level": "Bachelor\u0027s",
        "qualification": "BTECH/BE/BSC - Information Science / Computer Science / Mathematics / Statistics",
        "raw": "Bachelor\u2019s degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science.",
        "requirement": "required"
      }
    ],
    "experience": {
      "max": null,
      "min": 3,
      "raw": "Minimum of 3 years of experience as a data and API developer"
    },
    "job_locations": [
      {
        "aliases": [
          "Bengaluru"
        ],
        "city": "Bangalore",
        "country": "India",
        "state": null,
        "work_mode": "null"
      }
    ],
    "role": "Senior Cloud Data Engineer",
    "role_aliases": [
      "Cloud Data Engineer",
      "Data Engineer",
      "Senior Data Engineer"
    ],
    "role_archetype": "Data",
    "roles_and_responsibilities": [
      {
        "bullet_count": 0,
        "heading": "Responsibilities",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Working with the application teams",
          "last_5_words": "cost and service requirements."
        },
        "text": "Working with the application teams to prioritize new requests for functionality. Specifically, new user-facing functionality (e.g., the ability to ingest IoT data, subscription-based consumption, etc.)Addressing internal functionality (e.g., monitoring and alerting based on application performance, automated testing frameworks, etc.)Managing respective support queues (e.g., Ingest, Prepare, Storage and Consume, etc.) Note: agreed upon SLAs will be established post burn-in periodManage backlog via effective sprint planning based on feedback from the application teamsParticipating in monthly architecture review boardMentoring and coaching the application teams on tools, technology and design patternsEnsuring that the production environment is well built and that there is a clear escalation path for production issuesEnsuring solution architecture meets JLL\u0027s requirements including, but not limited to, those regarding cloud spend, scalability, performance, etc.Developing the framework components for JLL\u0027s cloud environmentDeveloping infrastructure that is scalable, reliable, and monitoredBuilding a relationship with Cloud providers, in order to take advantage of their most appropriate technology offeringsCollaborating with the application team leads to ensure that the application teams\u0027 needs are met through the CI/CD framework, component monitoring and stats, incident escalationInculcating \"infrastructure as code\" mentality in the Platform \\ team overallUtilizing Agile practices to manage and deliver features.Create and maintain incident management requests to product group/engineering group.Compare solution alternatives across both technical and business parameters which support the define cost and service requirements.",
        "word_count": 309
      },
      {
        "bullet_count": 0,
        "heading": "Experience \u0026 Education",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Bachelor\u2019s degree in Information Science",
          "last_5_words": "Agile with SCRUM, and Application"
        },
        "text": "Bachelor\u2019s degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science. Minimum of 3 years of experience as a data and API developer using Python/Nodejs, Azure Functions, Cosmos DB, Azure Event Hubs, Azure Data Lake Storage, Azure Storage Queues etc.Project experience leveraging Agile with SCRUM, and Application Lifecycle Management (ALM).",
        "word_count": 56
      },
      {
        "bullet_count": 0,
        "heading": "Technical Skills \u0026 Competencies",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "Excellent technical, analytical and organizational",
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}
API 2 — extract-details
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    {
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      "roles_from_db": []
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        {
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          "rationale": null,
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          "rationale": null,
          "role_archetype": null,
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        {
          "display_name": "Fullstack Developer",
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          "rationale": null,
          "role_archetype": null,
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        {
          "display_name": "Go Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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        {
          "display_name": "Java Backend Developer",
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          "rationale": null,
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          "display_name": "Kotlin Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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        {
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          "rationale": null,
          "role_archetype": null,
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        {
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          "rationale": null,
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          "slug": "ml-ops-engineer",
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        {
          "display_name": "Node.js Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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        {
          "display_name": "Python Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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        "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.",
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        "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.",
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        "source": "db"
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      "input_skill": "AWS",
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      "roles_from_db": [
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          "rationale": null,
          "role_archetype": null,
          "slug": "cybersecurity-engineer",
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    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Vendor Product Families",
        "id": 477,
        "rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
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        "source": "db"
      },
      "input_skill": "AWS",
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      "roles_from_db": [
        {
          "display_name": "Engineering Manager",
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    {
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        "rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
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        "source": "db"
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      "input_skill": "Azure",
      "llm_role": null,
      "roles_from_db": [
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          "display_name": ".NET Backend Developer",
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        {
          "display_name": "Go Backend Developer",
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          "rationale": null,
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        {
          "display_name": "Java Backend Developer",
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          "role_archetype": "Engineering",
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          "display_name": "Kotlin Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "kotlin-server-backend-developer",
          "source": "db"
        },
        {
          "display_name": "ML Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
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        {
          "display_name": "MLOps Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
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          "display_name": "Node.js Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
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        {
          "display_name": "Python Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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        {
          "display_name": "Scala Backend Developer",
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          "rationale": null,
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        "display_name": "Cloud Platforms \u0026 Managed Services",
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        "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": "Vendor Product Families",
        "id": 477,
        "rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
        "slug": "vendor-product-families",
        "source": "db"
      },
      "input_skill": "Azure",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Engineering Manager",
          "id": 121,
          "rationale": null,
          "role_archetype": null,
          "slug": "engineering-manager",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Microservices and Distributed Systems",
        "id": 9,
        "rationale": "Architectural patterns for decomposed backend systems and the operational concerns they introduce. Covers service boundaries, consistency tradeoffs, retries, circuit breakers, and distributed coordination.",
        "slug": "microservices-and-distributed-systems",
        "source": "db"
      },
      "input_skill": "Microservices",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Backend Developer",
          "id": 1,
          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
          "source": "db"
        },
        {
          "display_name": "Node.js Backend Developer",
          "id": 82,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Scala Backend Developer",
          "id": 87,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "scala-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Batch Ingestion and Replication",
        "id": 29,
        "rationale": "Moving data from source systems into landing zones or warehouses on batch schedules. Covers file ingestion, CDC-style replication, incremental loads, and source-to-target synchronization.",
        "slug": "batch-ingestion-and-replication",
        "source": "db"
      },
      "input_skill": "File ingestion",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Data Lineage and Metadata",
        "id": 28,
        "rationale": "Cataloging, documenting, and tracing how data moves and changes across systems. This dimension supports impact analysis, governance, discoverability, and operational understanding of datasets.",
        "slug": "data-lineage-and-metadata",
        "source": "db"
      },
      "input_skill": "Metadata management",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Observability and Incident Triage",
        "id": 155,
        "rationale": "Telemetry, alerting, and troubleshooting practices used to diagnose failed builds, broken deployments, and unhealthy release environments. This is a coherent cluster because delivery reliability depends on quickly identifying where the workflow failed.",
        "slug": "observability-and-incident-triage",
        "source": "db"
      },
      "input_skill": "Monitoring",
      "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": "Asynchronous Messaging and Event Streaming",
        "id": 297,
        "rationale": "Asynchronous communication patterns and broker technologies used to decouple backend services and move work off the request path. Includes queues, pub/sub, event streams, consumer groups, dead-letter queues, and delivery semantics across systems such as Kafka, RabbitMQ, NATS, SQS/SNS, Pulsar, and ActiveMQ.",
        "slug": "asynchronous-messaging-and-event-streaming",
        "source": "db"
      },
      "input_skill": "Pub/Sub",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": ".NET Backend Developer",
          "id": 83,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "dotnet-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Go Backend Developer",
          "id": 81,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "go-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Kotlin Backend Developer",
          "id": 84,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "kotlin-server-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Node.js Backend Developer",
          "id": 82,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
          "source": "db"
        },
        {
          "display_name": "Scala Backend Developer",
          "id": 87,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "scala-backend-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "RDBMS",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "CI/CD Pipeline Platforms",
        "id": 150,
        "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": "Azure DevOps",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "DevOps Engineer",
          "id": 10,
          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Primary implementation languages and runtime features used to build backend service logic in the .NET ecosystem. This is the core coding surface for request handling, domain logic, and service internals.",
        "slug": "c-and-net-languages",
        "source": "db"
      },
      "input_skill": "C#",
      "llm_role": null,
      "roles_from_db": [
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          "display_name": ".NET Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
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          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cross-Platform App Languages",
        "id": 167,
        "rationale": "Languages used to implement shared mobile features across iOS and Android from a common codebase. This is the primary coding surface for hybrid app logic, UI behavior, and platform-specific branching.",
        "slug": "cross-platform-app-languages",
        "source": "db"
      },
      "input_skill": "C#",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Hybrid Mobile Developer",
          "id": 11,
          "rationale": null,
          "role_archetype": null,
          "slug": "hybrid-mobile-developer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages",
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        "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
        "slug": "programming-languages",
        "source": "db"
      },
      "input_skill": "C#",
      "llm_role": null,
      "roles_from_db": [
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          "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": 435,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "fullstack-developer",
          "source": "db"
        },
        {
          "display_name": "Fullstack Developer",
          "id": 15,
          "rationale": null,
          "role_archetype": null,
          "slug": "full-stack-engineer",
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        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages for ML Systems",
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        "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
        "slug": "programming-languages-for-ml-systems",
        "source": "db"
      },
      "input_skill": "C#",
      "llm_role": null,
      "roles_from_db": [
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          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "MLOps Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages for XR",
        "id": 97,
        "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
        "slug": "programming-languages-for-xr",
        "source": "db"
      },
      "input_skill": "C#",
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      "roles_from_db": [
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          "display_name": "AR/VR Engineer",
          "id": 8,
          "rationale": null,
          "role_archetype": null,
          "slug": "ar-vr-engineer",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "C#",
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      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Sitecore Development Languages",
        "id": 438,
        "rationale": "Core implementation languages and markup used to build Sitecore customizations, rendering logic, and site behavior. This is the primary authoring surface for Sitecore-specific code and templates.",
        "slug": "sitecore-development-languages",
        "source": "db"
      },
      "input_skill": "C#",
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      "roles_from_db": [
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          "display_name": "Sitecore Dev",
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          "rationale": null,
          "role_archetype": "Engineering",
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          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Video Codec Languages and DSLs",
        "id": 225,
        "rationale": "Implementation languages and codec-specific description languages used to build compression, decoding, and transform logic. This is the primary coding surface for codec behavior and bitstream manipulation.",
        "slug": "video-codec-languages-and-dsls",
        "source": "db"
      },
      "input_skill": "C#",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Video Codec Engineer",
          "id": 22,
          "rationale": null,
          "role_archetype": null,
          "slug": "video-codec-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Storage and Data Services",
        "id": 144,
        "rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
        "slug": "cloud-storage-and-data-services",
        "source": "db"
      },
      "input_skill": "Azure Table Storage",
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      "roles_from_db": [
        {
          "display_name": "Cloud Architect",
          "id": 9,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-architect",
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        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Cloud Storage and File Formats",
        "id": 35,
        "rationale": "Object storage and data file formats used as the physical substrate for data movement and lake-style analytics. Data engineers need these to manage landing zones, partitioned datasets, and efficient interchange.",
        "slug": "cloud-storage-and-file-formats",
        "source": "db"
      },
      "input_skill": "Azure Table Storage",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
          "id": 2,
          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Search and Content Discovery",
        "id": 356,
        "rationale": "Implementing site search, indexing, and content discovery features in Drupal. This cluster is coherent because many Drupal sites need structured search experiences beyond basic navigation.",
        "slug": "search-and-content-discovery",
        "source": "db"
      },
      "input_skill": "Azure AI Search",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Drupal Dev",
          "id": 228,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "drupal-dev",
          "source": "db"
        },
        {
          "display_name": "Sitecore Dev",
          "id": 233,
          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "sitecore-dev",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "CI/CD Pipeline Platforms",
        "id": 150,
        "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": "CI/CD",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "DevOps Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "devops-engineer",
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        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "CI/CD for Machine Learning",
        "id": 56,
        "rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
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        "source": "db"
      },
      "input_skill": "CI/CD",
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      "roles_from_db": [
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          "display_name": "ML Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
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      ]
    },
    {
      "dimension": {
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        "display_name": "Delivery Planning and Execution",
        "id": 461,
        "rationale": "Coordinates how work gets done across the team, including sequencing, commitments, dependencies, and follow-through. This cluster is coherent because EMs are accountable for predictable delivery rather than the technical implementation itself.",
        "slug": "delivery-planning-and-execution",
        "source": "db"
      },
      "input_skill": "Sprint Planning",
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      "roles_from_db": [
        {
          "display_name": "Engineering Manager",
          "id": 121,
          "rationale": null,
          "role_archetype": null,
          "slug": "engineering-manager",
          "source": "db"
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      ]
    }
  ],
  "input_final_skills": [
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  "input_llm_skills": [
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    "Azure SignalR",
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  "new_aliases_persisted": 0,
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  "skills_detail": [
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          "alias_text": "Python",
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          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Python 2",
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        },
        {
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        {
          "alias_text": "Python 3",
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        },
        {
          "alias_text": "Python 3.10",
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          "id": 5892,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 11,
        "display_name": "Azure Cognitive Search",
        "id": 4169,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CLOUD_SERVICE",
        "slug": "azure-cognitive-search",
        "sub_category_id": 3308,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Search and Content Discovery",
            "id": 356,
            "rationale": "Implementing site search, indexing, and content discovery features in Drupal. This cluster is coherent because many Drupal sites need structured search experiences beyond basic navigation.",
            "slug": "search-and-content-discovery",
            "source": "db"
          },
          "input_skill": "Azure AI Search",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Drupal Dev",
              "id": 228,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "drupal-dev",
              "source": "db"
            },
            {
              "display_name": "Sitecore Dev",
              "id": 233,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "sitecore-dev",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Azure AI Search",
      "matched_via": "embedding_alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Azure SignalR",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Cloud Platforms",
          "skill_nature": "PLATFORM",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "azure-signalr",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Infrastructure as Code",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Practices",
          "skill_nature": "PRACTICE",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "infrastructure-as-code",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "CI/CD",
          "alias_type": "CANONICAL",
          "id": 1826,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "CI/CD",
        "id": 1190,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "ci-cd",
        "sub_category_id": 900,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "CI/CD Pipeline Platforms",
            "id": 150,
            "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": "CI/CD",
          "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": "CI/CD for Machine Learning",
            "id": 56,
            "rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
            "slug": "ci-cd-for-machine-learning",
            "source": "db"
          },
          "input_skill": "CI/CD",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "CI/CD",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Incident Management",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Practices",
          "skill_nature": "PRACTICE",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "incident-management",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "sprint planning",
          "alias_type": "CANONICAL",
          "id": 6399,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "sprint planning",
        "id": 4550,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "sprint-planning",
        "sub_category_id": 3628,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Delivery Planning and Execution",
            "id": 461,
            "rationale": "Coordinates how work gets done across the team, including sequencing, commitments, dependencies, and follow-through. This cluster is coherent because EMs are accountable for predictable delivery rather than the technical implementation itself.",
            "slug": "delivery-planning-and-execution",
            "source": "db"
          },
          "input_skill": "Sprint Planning",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Engineering Manager",
              "id": 121,
              "rationale": null,
              "role_archetype": null,
              "slug": "engineering-manager",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Sprint Planning",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Azure Event Hubs",
    "Azure Storage Queues",
    "Application Lifecycle Management",
    "Cloud Computing",
    "Streaming Technologies",
    "Network",
    "Security",
    "API ingestion",
    "Batch transformation",
    "Real-time transformation",
    "Octopus Deploy",
    "APIM",
    "Azure Monitor",
    "Azure Databricks",
    "Azure SQL Database",
    "Azure SignalR",
    "Infrastructure as Code",
    "Incident Management"
  ]
}
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 backend-engineer 0.19 does not contradict",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "Node.js",
      "tag": "in_db"
    },
    {
      "skill": "Azure Functions",
      "tag": "in_db"
    },
    {
      "skill": "Cosmos DB",
      "tag": "in_db"
    },
    {
      "skill": "Azure Event Hubs",
      "tag": "new"
    },
    {
      "skill": "Azure Data Lake Storage",
      "tag": "in_db"
    },
    {
      "skill": "Azure Storage Queues",
      "tag": "new"
    },
    {
      "skill": "Agile",
      "tag": "in_db"
    },
    {
      "skill": "Scrum",
      "tag": "in_db"
    },
    {
      "skill": "Application Lifecycle Management",
      "tag": "new"
    },
    {
      "skill": "Cloud Computing",
      "tag": "new"
    },
    {
      "skill": "AWS",
      "tag": "in_db"
    },
    {
      "skill": "Azure",
      "tag": "in_db"
    },
    {
      "skill": "Microservices",
      "tag": "in_db"
    },
    {
      "skill": "Streaming Technologies",
      "tag": "new"
    },
    {
      "skill": "Network",
      "tag": "new"
    },
    {
      "skill": "Security",
      "tag": "new"
    },
    {
      "skill": "API ingestion",
      "tag": "new"
    },
    {
      "skill": "File ingestion",
      "tag": "in_db"
    },
    {
      "skill": "Batch transformation",
      "tag": "new"
    },
    {
      "skill": "Metadata management",
      "tag": "in_db"
    },
    {
      "skill": "Monitoring",
      "tag": "in_db"
    },
    {
      "skill": "Pub/Sub",
      "tag": "in_db"
    },
    {
      "skill": "RDBMS",
      "tag": "in_db"
    },
    {
      "skill": "Real-time transformation",
      "tag": "new"
    },
    {
      "skill": "Octopus Deploy",
      "tag": "new"
    },
    {
      "skill": "Azure DevOps",
      "tag": "in_db"
    },
    {
      "skill": "C#",
      "tag": "in_db"
    },
    {
      "skill": "APIM",
      "tag": "new"
    },
    {
      "skill": "Azure Monitor",
      "tag": "new"
    },
    {
      "skill": "Azure Table Storage",
      "tag": "in_db"
    },
    {
      "skill": "Azure Databricks",
      "tag": "new"
    },
    {
      "skill": "Azure SQL Database",
      "tag": "new"
    },
    {
      "skill": "Azure AI Search",
      "tag": "in_db"
    },
    {
      "skill": "Azure SignalR",
      "tag": "new"
    },
    {
      "skill": "Infrastructure as Code",
      "tag": "new"
    },
    {
      "skill": "CI/CD",
      "tag": "in_db"
    },
    {
      "skill": "Incident Management",
      "tag": "new"
    },
    {
      "skill": "Sprint Planning",
      "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 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": 435,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "fullstack-developer",
            "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 \u0026 DSLs",
          "id": 475,
          "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
          "slug": "programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 475,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages and Scripting",
          "id": 59,
          "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
          "slug": "programming-languages-and-scripting",
          "source": "db"
        },
        "dimension_id": 59,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for Data Work",
          "id": 21,
          "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
        "dimension_id": 21,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for ML Systems",
          "id": 39,
          "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
          "slug": "programming-languages-for-ml-systems",
          "source": "db"
        },
        "dimension_id": 39,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for XR",
          "id": 97,
          "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
          "slug": "programming-languages-for-xr",
          "source": "db"
        },
        "dimension_id": 97,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AR/VR Engineer",
            "id": 8,
            "rationale": null,
            "role_archetype": null,
            "slug": "ar-vr-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Python Programming",
          "id": 290,
          "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
          "slug": "python-programming",
          "source": "db"
        },
        "dimension_id": 290,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "JavaScript and TypeScript",
          "id": 114,
          "rationale": "Primary implementation languages for browser client code, UI logic, and shared frontend utilities. These languages are the main coding surface for building interactive web experiences in this role.",
          "slug": "javascript-and-typescript",
          "source": "db"
        },
        "dimension_id": 114,
        "input_skill": "Node.js",
        "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": "Angular Frontend Developer",
            "id": 90,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "angular-frontend-developer",
            "source": "db"
          },
          {
            "display_name": "Frontend Developer",
            "id": 7,
            "rationale": null,
            "role_archetype": null,
            "slug": "frontend-engineer",
            "source": "db"
          },
          {
            "display_name": "Ionic Developer",
            "id": 434,
            "rationale": null,
            "role_archetype": null,
            "slug": "ionic-developer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
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          },
          {
            "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": "Vendor Product Families",
          "id": 477,
          "rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
          "slug": "vendor-product-families",
          "source": "db"
        },
        "dimension_id": 477,
        "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": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "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": "Microservices and Distributed Systems",
          "id": 9,
          "rationale": "Architectural patterns for decomposed backend systems and the operational concerns they introduce. Covers service boundaries, consistency tradeoffs, retries, circuit breakers, and distributed coordination.",
          "slug": "microservices-and-distributed-systems",
          "source": "db"
        },
        "dimension_id": 9,
        "input_skill": "Microservices",
        "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": "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": 41,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Batch Ingestion and Replication",
          "id": 29,
          "rationale": "Moving data from source systems into landing zones or warehouses on batch schedules. Covers file ingestion, CDC-style replication, incremental loads, and source-to-target synchronization.",
          "slug": "batch-ingestion-and-replication",
          "source": "db"
        },
        "dimension_id": 29,
        "input_skill": "File ingestion",
        "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": 143,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Data Lineage and Metadata",
          "id": 28,
          "rationale": "Cataloging, documenting, and tracing how data moves and changes across systems. This dimension supports impact analysis, governance, discoverability, and operational understanding of datasets.",
          "slug": "data-lineage-and-metadata",
          "source": "db"
        },
        "dimension_id": 28,
        "input_skill": "Metadata management",
        "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": 137,
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        "skipped_reason": null
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      {
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          "difficulty_hint": "well_known",
          "display_name": "Observability and Incident Triage",
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          "rationale": "Telemetry, alerting, and troubleshooting practices used to diagnose failed builds, broken deployments, and unhealthy release environments. This is a coherent cluster because delivery reliability depends on quickly identifying where the workflow failed.",
          "slug": "observability-and-incident-triage",
          "source": "db"
        },
        "dimension_id": 155,
        "input_skill": "Monitoring",
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        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1218,
        "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": "Pub/Sub",
        "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": 2443,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "RDBMS",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1355,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD Pipeline Platforms",
          "id": 150,
          "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"
        },
        "dimension_id": 150,
        "input_skill": "Azure DevOps",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "DevOps Engineer",
            "id": 10,
            "rationale": null,
            "role_archetype": null,
            "slug": "devops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1214,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "C# and .NET Languages",
          "id": 362,
          "rationale": "Primary implementation languages and runtime features used to build backend service logic in the .NET ecosystem. This is the core coding surface for request handling, domain logic, and service internals.",
          "slug": "c-and-net-languages",
          "source": "db"
        },
        "dimension_id": 362,
        "input_skill": "C#",
        "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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 4,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cross-Platform App Languages",
          "id": 167,
          "rationale": "Languages used to implement shared mobile features across iOS and Android from a common codebase. This is the primary coding surface for hybrid app logic, UI behavior, and platform-specific branching.",
          "slug": "cross-platform-app-languages",
          "source": "db"
        },
        "dimension_id": 167,
        "input_skill": "C#",
        "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": "Hybrid Mobile Developer",
            "id": 11,
            "rationale": null,
            "role_archetype": null,
            "slug": "hybrid-mobile-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 4,
        "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": "C#",
        "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": 435,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "fullstack-developer",
            "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": 4,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for ML Systems",
          "id": 39,
          "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
          "slug": "programming-languages-for-ml-systems",
          "source": "db"
        },
        "dimension_id": 39,
        "input_skill": "C#",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 4,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for XR",
          "id": 97,
          "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
          "slug": "programming-languages-for-xr",
          "source": "db"
        },
        "dimension_id": 97,
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        ],
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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          "slug": "sitecore-development-languages",
          "source": "db"
        },
        "dimension_id": 438,
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [
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        ],
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        },
        "dimension_id": 225,
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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        "roles_from_db": [
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        ],
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          "display_name": "Cloud Storage and Data Services",
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          "rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
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          "source": "db"
        },
        "dimension_id": 144,
        "input_skill": "Azure Table Storage",
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        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
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        "roles_from_db": [
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            "display_name": "Cloud Architect",
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        ],
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        "chosen_role_id": 2,
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        "matched_chosen_role": true,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
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        "roles_from_db": [
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        ],
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          "display_name": "Search and Content Discovery",
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          "rationale": "Implementing site search, indexing, and content discovery features in Drupal. This cluster is coherent because many Drupal sites need structured search experiences beyond basic navigation.",
          "slug": "search-and-content-discovery",
          "source": "db"
        },
        "dimension_id": 356,
        "input_skill": "Azure AI Search",
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        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
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        "roles_from_db": [
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            "display_name": "Drupal Dev",
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            "source": "db"
          },
          {
            "display_name": "Sitecore Dev",
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            "role_archetype": "Engineering",
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            "source": "db"
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        ],
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          "rationale": "Coordinates how work gets done across the team, including sequencing, commitments, dependencies, and follow-through. This cluster is coherent because EMs are accountable for predictable delivery rather than the technical implementation itself.",
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        "roles_from_db": [
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            "display_name": "Engineering Manager",
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            "slug": "engineering-manager",
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        "skill_id": 4550,
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}