Pipeline run
6b2c6d2f-fe99-4e62-9f9c-243fe26825e7
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
Captured for admin review
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Data Engineer
CASE Aslug: 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.
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 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’s 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. For more information about how JLL processes your personal data, please view our Candidate Privacy Statement. For additional details please see our career site pages for each country. For employees in the United States, please see a fully copy of our Equal Employment Opportunity and Affirmative Action policy here. 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.
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)
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) |
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)
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) |
Aliases — catalog
- Azure Functions (CANONICAL) primary
Context tags (catalog)
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) |
Aliases — catalog
- Cosmos DB (CANONICAL)
Context tags (catalog)
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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- Message Brokers
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Azure Blob Storage (CANONICAL) primary
Context tags (catalog)
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
|
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- Message Brokers
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Agile (CANONICAL) primary
Context tags (catalog)
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) |
Aliases — catalog
- Scrum (CANONICAL) primary
Context tags (catalog)
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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Practices
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Aliases — catalog
- AWS (CANONICAL) primary
Context tags (catalog)
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) |
Aliases — catalog
- Azure (CANONICAL) primary
Context tags (catalog)
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) |
Aliases — catalog
- microservices (CANONICAL) primary
Context tags (catalog)
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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- File ingestion (CANONICAL) primary
Context tags (catalog)
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 |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Metadata management (CANONICAL) primary
Context tags (catalog)
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 |
Aliases — catalog
- Monitoring (CANONICAL)
Context tags (catalog)
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) |
Aliases — catalog
- pub/sub (CANONICAL) primary
Context tags (catalog)
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) |
Aliases — catalog
- RDBMS (CANONICAL)
Context tags (catalog)
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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- DevOps Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Azure DevOps (CANONICAL)
Context tags (catalog)
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) |
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)
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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- API Management
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- Monitoring Tools
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Azure Blob Storage (CANONICAL) primary
Context tags (catalog)
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
|
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- Machine Learning Frameworks
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- Databases
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Azure Cognitive Search (CANONICAL) primary
Context tags (catalog)
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
|
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Practices
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- CI/CD (CANONICAL)
Context tags (catalog)
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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Practices
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- sprint planning (CANONICAL) primary
Context tags (catalog)
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
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": {
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"aliases": [
"Tech Consulting",
"Cloud Services"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [
{
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"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,
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"Tech Consulting",
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],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
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"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": {
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"raw": "Minimum of 3 years of experience as a data and API developer"
},
"job_locations": [
{
"aliases": [
"Bengaluru"
],
"city": "Bangalore",
"country": "India",
"state": null,
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}
],
"role": "Senior Cloud Data Engineer",
"role_aliases": [
"Cloud Data Engineer",
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"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.",
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},
{
"bullet_count": 0,
"heading": "Experience \u0026 Education",
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"source_marker": {
"first_5_words": "Bachelor\u2019s degree in Information Science",
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},
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"heading": "Technical Skills \u0026 Competencies",
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"source_marker": {
"first_5_words": "Excellent technical, analytical and organizational",
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},
"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": []
},
"rejected": false,
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"run_id": "6b2c6d2f-fe99-4e62-9f9c-243fe26825e7",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
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"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 1.0,
"slug": "data-engineer",
"total_count": null
}
],
"kra_match_roles": [
{
"display_name": "Cloud Architect",
"kra_matches": [
{
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"sentence": "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.",
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],
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},
{
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{
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},
{
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},
{
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],
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},
{
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{
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},
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API 2 — extract-details
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],
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{
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]
},
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]
},
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},
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]
},
{
"dimension": {
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},
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]
},
{
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},
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},
{
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},
{
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},
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{
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},
{
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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,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "React Frontend Developer",
"id": 89,
"rationale": null,
"role_archetype": "Engineering",
"slug": "react-frontend-developer",
"source": "db"
},
{
"display_name": "React Native Developer",
"id": 73,
"rationale": null,
"role_archetype": "Engineering",
"slug": "react-native-developer",
"source": "db"
},
{
"display_name": "Svelte Frontend Developer",
"id": 92,
"rationale": null,
"role_archetype": "Engineering",
"slug": "svelte-frontend-developer",
"source": "db"
},
{
"display_name": "Vue Frontend Developer",
"id": 91,
"rationale": null,
"role_archetype": "Engineering",
"slug": "vue-frontend-developer",
"source": "db"
},
{
"display_name": "Web Developer",
"id": 25,
"rationale": null,
"role_archetype": null,
"slug": "web-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1564,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Web Application Frameworks",
"id": 2,
"rationale": "Server frameworks and runtimes used to build HTTP services, controllers, middleware, and request pipelines. These frameworks shape how backend endpoints are structured and delivered.",
"slug": "web-application-frameworks",
"source": "db"
},
"dimension_id": 2,
"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": "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",
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"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,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"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"
},
"dimension_id": 155,
"input_skill": "Monitoring",
"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": 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,
"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": "AR/VR Engineer",
"id": 8,
"rationale": null,
"role_archetype": null,
"slug": "ar-vr-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": "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": "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": [],
"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": "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"
},
"dimension_id": 438,
"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": "Sitecore Dev",
"id": 233,
"rationale": null,
"role_archetype": "Engineering",
"slug": "sitecore-dev",
"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": "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"
},
"dimension_id": 225,
"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": "Video Codec Engineer",
"id": 22,
"rationale": null,
"role_archetype": null,
"slug": "video-codec-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": "Cloud Storage and Data Services",
"id": 144,
"rationale": "Cloud-native storage and managed data services used to place workloads, choose durability tiers, and define platform boundaries. This is a coherent cluster because architects evaluate storage fit, access patterns, and managed service tradeoffs.",
"slug": "cloud-storage-and-data-services",
"source": "db"
},
"dimension_id": 144,
"input_skill": "Azure Table Storage",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": null,
"skill_tag": "new",
"skipped_reason": "skill_not_in_db_v3_proposed"
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Storage and File Formats",
"id": 35,
"rationale": "Object storage and data file formats used as the physical substrate for data movement and lake-style analytics. Data engineers need these to manage landing zones, partitioned datasets, and efficient interchange.",
"slug": "cloud-storage-and-file-formats",
"source": "db"
},
"dimension_id": 35,
"input_skill": "Azure Table Storage",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": null,
"skill_tag": "new",
"skipped_reason": "skill_not_in_db_v3_proposed"
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Search and Content Discovery",
"id": 356,
"rationale": "Implementing site search, indexing, and content discovery features in Drupal. This cluster is coherent because many Drupal sites need structured search experiences beyond basic navigation.",
"slug": "search-and-content-discovery",
"source": "db"
},
"dimension_id": 356,
"input_skill": "Azure AI Search",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "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"
}
],
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