Pipeline run
7e6d1eb9-d6ff-4628-9e52-707b7980249a
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
domain · Data Engineering & Analytics CASE DOMAINslug: data-engineer · id: 2 · source: db
Domain=Data Engineering & Analytics; The JD is centered on cloud data platform architecture, reusable/scalable data pipelines, Databricks, and AWS-based data engineering, which best matches Data Engineer.
Matched skills
Matched dimensions
Matched KRAs
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Date Posted: 2024-08-01 Country: India Location: North Gate Business Park Sy.No 2/1, and Sy.No 2/2, KIAL Road, Venkatala Village, Chowdeshwari Layout, Yelahanka, Bangalore, Karnataka 560064 Position Role Type: Unspecified Job Title: Senior Lead Engineer Primary Responsibilities: • You will be responsible to understand the client requirement and architect robust data platform on cloud technologies (AWS). • You will be responsible for creating reusable and scalable data pipelines. • You will be responsible for development and deployment of new data platforms. Basic Qualifications: • 10+ years of technology experience in Software Development Life Cycle • Above includes 3+ years as Project Lead, Architect • Bachelor's Degree (required) and 10+ years’ experience; or Master’s Degree (preferred) and 7+ years’ experience. Preferred fields include Computer Science, Engineering, MIS, or related business discipline(s) Preferred Qualifications: • Collaborate with the stakeholders to gather and prioritize the product requirements • Create and manage product backlog • Strong experience in Agile Methodology (SAFE Agile) • Experience using JIRA or other equivalent tools to create requirements and task management tool • Work closely with the development teams to ensure timely and successful releases and deliverables • Develop detailed user stories, acceptance criteria and wireframes • Act as a bridge between business stakeholders, management, and development teams to facilitate effective communication • Drive the team towards delivering products that meet customer expectations • Work with other development teams to manage dependencies and risks • Good knowledge in Python & PySpark are preferred • Experience in AWS cloud and AWS services such as S3 Buckets, Lambda, API Gateway, SQS queues, Glue, Kinesis, DynamoDB, Athena etc. (preferred) • Experience with data engineering using Databricks (Mandatory) • Knowledge in DevOps CI/CD tools, such Git, Jenkins, Linux, AWS Code Commit, Build & Deploy • Knowledge in Security, performance, and Project compliance and processes • Excellent problem-solving skills • Excellent communication skills • Experience working with distributed teams across multiple time zones • Ability to explain a concept with clarity to the present stakeholders Ability to provide coaching and guidance to juniors Collins Aerospace, a Raytheon Technologies company, is a leader in technologically advanced and intelligent solutions for the global aerospace and defense industry. Collins Aerospace has the capabilities, comprehensive portfolio and expertise to solve customers’ toughest challenges and to meet the demands of a rapidly evolving global market. Our Avionics team advances aviation electronics and information management solutions for commercial and military customers across the world. That means we’re helping passengers reach their destination safely. We’re connecting aircraft operators, airports, rail and critical infrastructure with intelligent data service solutions that keep passengers, flight crews and militaries connected and informed. And we’re providing industry-leading fire protection and safety systems that our customers can count on when it matters most. Are you ready to learn from the most knowledgeable experts in the industry, develop the technologies of tomorrow and reach new heights in your career? Join our Avionics team today. Diversity drives innovation; inclusion drives success. We believe a multitude of approaches and ideas enable us to deliver the best results for our workforce, workplace, and customers. We are committed to fostering a culture where all employees can share their passions and ideas so we can tackle the toughest challenges in our industry and pave new paths to limitless possibility. WE ARE REDEFINING AEROSPACE. Hybrid: Employees who are working in Hybrid roles will work regularly both onsite and offsite. Ratio of time working onsite will be determined in partnership with your leader. Some of our competitive benefits package includes: Benefits package includes: • Transportation facility. • Meal coupons • Group Term Life Insurance. • Group Health Insurance. • Group Personal Accident Insurance. • Entitled for 18 days of vacation and 7 days of contingency leave annually. • Employee scholar program. • Work life balance. • Car lease program. • National Pension Scheme • LTA • Fuel & Maintenance /Driver wages • Meal vouchers Nothing matters more to Collins Aerospace than our strong ethical and safety commitments. As such, all India positions require a background check, which may include a drug screen. Note: • Background check required (every external new hire in the India) • Drug Screen only performed for Operations Positions At Collins, the paths we pave together lead to limitless possibility. And the bonds we form – with our customers and with each other -- propel us all higher, again and again. Apply now and be part of the team that’s redefining aerospace, every day RTX is An Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class. Privacy Policy and Terms: Click on this link to read the Policy and Terms
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
- 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
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) |
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 and Scripting Catalog dimension db id 59
Library dimension (catalog)
Roles linked in library: Cyber Security Engineer
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
-
Programming Languages for ML Systems Catalog dimension db id 39
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
-
Programming Languages for XR Catalog dimension db id 97
Library dimension (catalog)
Roles linked in library: AR/VR Engineer
-
Python Programming Catalog dimension db id 290
Library dimension (catalog)
Roles linked in library: Python Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Python Programming
python-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Apache Spark (CANONICAL)
- apache spark 3 (VERSION)
- spark (VERSION)
- spark 3 (VERSION)
- spark 3.x (VERSION)
- spark3 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Distributed Data Processing Framework
- Vendor
- Apache Software Foundation
- License
- apache_2
- Year introduced
- 2010
- Confidence
- 0.94
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 3.x
Maturity reasoning: Apache Spark appears in many data engineering JDs and remains a standard for distributed ETL/ELT; its GitHub and vendor ecosystem activity stay strong, with Databricks and cloud platforms still promoting it.
Skill profile (library / DB)
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 5
- Sub-category id
- 1021
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
ETL and ELT Tooling Catalog dimension db id 24
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
ETL and ELT Tooling
etl-and-elt-tooling
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
Aliases — catalog
- S3 (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Cloud Storage Platform
- Vendor
- Amazon
- License
- proprietary
- Year introduced
- 2006
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Amazon S3 is a default cloud storage service in AWS job descriptions and architecture docs; it remains broadly adopted with no vendor sunset, and is commonly paired with S3-compatible storage rather than replaced.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 919
- 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
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
-
Systems Programming Catalog dimension db id 166
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Systems Programming
d_init_02
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- AWS Lambda (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Service
- Sub-category
- Serverless Function Service
- Vendor
- Amazon Web Services
- License
- other_open
- Year introduced
- 2014
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Broadly listed in cloud/backend JDs and AWS’s serverless docs/marketplace; it’s a standard 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
- 1704
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Platforms Catalog dimension db id 20
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer
-
Cloud Platforms & Hosting Providers Catalog dimension db id 278
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Kotlin Backend Developer, Scala Backend Developer, Web Developer
-
Cloud Platforms & Managed Services Catalog dimension db id 221
Library dimension (catalog)
Roles linked in library: Fullstack Developer, Go Backend Developer, Node.js Backend Developer
-
Cloud Platforms & Services Catalog dimension db id 296
Library dimension (catalog)
Roles linked in library: Python Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Platforms & Managed Services
cloud-platforms-managed-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Platforms & Services
cloud-platforms-services
|
✓ | — | 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
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- SQS (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Service
- Sub-category
- Message Queue Service
- Vendor
- Amazon Web Services
- License
- proprietary
- Year introduced
- 2010
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: AWS SQS is a standard cloud message queue, commonly listed in backend/DevOps JDs and widely used in production on AWS; no vendor sunset or replacement signal exists.
Skill profile (library / DB)
- Skill nature
- CLOUD_SERVICE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 11
- Sub-category id
- 56
- 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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- Data Engineering Tools
- 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
- Message Brokers
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Amazon DynamoDB (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Service
- Sub-category
- Managed Nosql Database Service
- Vendor
- Amazon Web Services
- License
- proprietary
- Year introduced
- 2012
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Commonly listed in cloud/backend job descriptions and widely used on AWS; strong vendor adoption and active ecosystem signal broad market demand.
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
|
— | — |
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
- Data Engineering Tools
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Databricks (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Data Analytics Platform
- Vendor
- Databricks, Inc.
- License
- other_open
- Year introduced
- 2013
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Databricks appears frequently in data engineering and analytics job postings, especially alongside Spark, Delta Lake, and lakehouse stacks; strong vendor adoption and broad enterprise usage signal mainstream demand.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 911
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
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
- 367
- 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
- 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
- Project Management Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Git (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Tool
- Sub-category
- Version Control Tool
- Vendor
- Linus Torvalds
- License
- gpl_v2
- Year introduced
- 2005
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Git is a hiring-pipeline staple: it appears in the vast majority of software engineering job descriptions and is the default VCS on GitHub/GitLab/Bitbucket.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 13
- Sub-category id
- 730
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Jenkins (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Tool
- Sub-category
- Ci Cd Tool
- Vendor
- CloudBees
- License
- mit
- Year introduced
- 2011
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Jenkins remains a common CI/CD requirement in job postings and enterprise DevOps stacks, with broad plugin ecosystem and long-running GitHub activity despite newer alternatives.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 13
- Sub-category id
- 184
- 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
- Operating Systems
- 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
- Cloud Platforms
- Sub-category
- Version Control
- Skill nature
- PLATFORM
- 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) |
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 |
|---|---|---|---|---|---|---|
| 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) | |
| Python | in_db |
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Python | in_db |
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Python Programming
python-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| PySpark | new |
ETL and ELT Tooling
etl-and-elt-tooling
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| S3 | in_db |
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| S3 | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| S3 | in_db |
Systems Programming
d_init_02
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS Lambda | in_db |
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| AWS Lambda | in_db |
Cloud Platforms & Hosting Providers
cloud-platforms-hosting-providers
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS Lambda | in_db |
Cloud Platforms & Managed Services
cloud-platforms-managed-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS Lambda | in_db |
Cloud Platforms & Services
cloud-platforms-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| SQS | in_db |
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DynamoDB | new |
NoSQL Databases
nosql-databases
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Databricks | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Agile | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Git | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Jenkins | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Jenkins | in_db |
CI/CD for Machine Learning
ci-cd-for-machine-learning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| CI/CD | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| CI/CD | in_db |
CI/CD for Machine Learning
ci-cd-for-machine-learning
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | API Gateway | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | AWS Glue | type=Cloud Platforms subtype=Data Engineering Tools nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Kinesis | type=Cloud Platforms subtype=Message Brokers nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Athena | type=Cloud Platforms subtype=Data Engineering Tools nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | SAFe Agile | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Jira | type=Project Management Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Linux | type=Operating Systems subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | AWS CodeCommit | type=Cloud Platforms subtype=Version Control nature=PLATFORM lifespan=MULTI_YEAR | |
| dimension_skill_link_proposed | PySpark ↔ ETL and ELT Tooling | |
| role_dimension_link_proposed | Data Engineer ↔ ETL and ELT Tooling | |
| dimension_skill_link_proposed | DynamoDB ↔ NoSQL Databases |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "Collins Aerospace, a Raytheon Technologies",
"last_5_words": "to limitless possibility."
},
"text": "Collins Aerospace, a Raytheon Technologies company, is a leader in technologically advanced and intelligent solutions for the global aerospace and defense industry. Collins Aerospace has the capabilities, comprehensive portfolio and expertise to solve customers\u2019 toughest challenges and to meet the demands of a rapidly evolving global market.\n\nOur Avionics team advances aviation electronics and information management solutions for commercial and military customers across the world. That means we\u2019re helping passengers reach their destination safely. We\u2019re connecting aircraft operators, airports, rail and critical infrastructure with intelligent data service solutions that keep passengers, flight crews and militaries connected and informed. And we\u2019re providing industry-leading fire protection and safety systems that our customers can count on when it matters most. Are you ready to learn from the most knowledgeable experts in the industry, develop the technologies of tomorrow and reach new heights in your career? Join our Avionics team today.\n\nDiversity drives innovation; inclusion drives success. We believe a multitude of approaches and ideas enable us to deliver the best results for our workforce, workplace, and customers. We are committed to fostering a culture where all employees can share their passions and ideas so we can tackle the toughest challenges in our industry and pave new paths to limitless possibility.",
"word_count": 211
},
"certifications": [],
"company_name": "Collins Aerospace",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"Aerospace",
"Defense"
],
"domain": "Aerospace \u0026 Defense"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE - Computer Science / Engineering / MIS (or related)",
"raw": "Bachelor\u0027s Degree (required) and 10+ years\u2019 experience; or Master\u2019s Degree (preferred) and 7+ years\u2019 experience.",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 7,
"raw": "10+ years of technology experience in Software Development Life Cycle"
},
"job_locations": [
{
"aliases": [
"Bengaluru"
],
"city": "Bangalore",
"country": "India",
"state": "Karnataka",
"work_mode": "hybrid"
}
],
"role": "Senior Lead Engineer",
"role_aliases": [
"Lead Engineer",
"Senior Engineer",
"Software Engineer"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 3,
"heading": "Primary Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 You will be responsible",
"last_5_words": "deployment of new data platforms."
},
"text": "\u2022 You will be responsible to understand the client requirement and architect robust data platform on cloud technologies (AWS).\n\u2022 You will be responsible for creating reusable and scalable data pipelines.\n\u2022 You will be responsible for development and deployment of new data platforms.",
"word_count": 36
},
{
"bullet_count": 3,
"heading": "Basic Qualifications",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 10+ years of technology experience",
"last_5_words": "or related business discipline(s)"
},
"text": "\u2022 10+ years of technology experience in Software Development Life Cycle\n\u2022 Above includes 3+ years as Project Lead, Architect\n\u2022 Bachelor\u0027s Degree (required) and 10+ years\u2019 experience; or Master\u2019s Degree (preferred) and 7+ years\u2019 experience. Preferred fields include Computer Science, Engineering, MIS, or related business discipline(s)",
"word_count": 45
},
{
"bullet_count": 18,
"heading": "Preferred Qualifications",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Collaborate with the stakeholders",
"last_5_words": "to the present stakeholders"
},
"text": "\u2022 Collaborate with the stakeholders to gather and prioritize the product requirements\n\u2022 Create and manage product backlog\n\u2022 Strong experience in Agile Methodology (SAFE Agile)\n\u2022 Experience using JIRA or other equivalent tools to create requirements and task management tool\n\u2022 Work closely with the development teams to ensure timely and successful releases and deliverables\n\u2022 Develop detailed user stories, acceptance criteria and wireframes\n\u2022 Act as a bridge between business stakeholders, management, and development teams to facilitate effective communication\n\u2022 Drive the team towards delivering products that meet customer expectations\n\u2022 Work with other development teams to manage dependencies and risks\n\u2022 Good knowledge in Python \u0026 PySpark are preferred\n\u2022 Experience in AWS cloud and AWS services such as S3 Buckets, Lambda, API Gateway, SQS queues, Glue, Kinesis, DynamoDB, Athena etc. (preferred)\n\u2022 Experience with data engineering using Databricks (Mandatory)\n\u2022 Knowledge in DevOps CI/CD tools, such Git, Jenkins, Linux, AWS Code Commit, Build \u0026 Deploy\n\u2022 Knowledge in Security, performance, and Project compliance and processes\n\u2022 Excellent problem-solving skills\n\u2022 Excellent communication skills\n\u2022 Experience working with distributed teams across multiple time zones\n\u2022 Ability to explain a concept with clarity to the present stakeholders",
"word_count": 233
},
{
"bullet_count": 0,
"heading": "Ability",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Ability to provide coaching",
"last_5_words": "coaching and guidance to juniors"
},
"text": "Ability to provide coaching and guidance to juniors",
"word_count": 10
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "AWS"
},
{
"is_primary": true,
"skill_name": "Python"
},
{
"is_primary": true,
"skill_name": "PySpark"
},
{
"is_primary": false,
"skill_name": "S3"
},
{
"is_primary": false,
"skill_name": "AWS Lambda"
},
{
"is_primary": false,
"skill_name": "API Gateway"
},
{
"is_primary": false,
"skill_name": "SQS"
},
{
"is_primary": false,
"skill_name": "AWS Glue"
},
{
"is_primary": false,
"skill_name": "Kinesis"
},
{
"is_primary": false,
"skill_name": "DynamoDB"
},
{
"is_primary": false,
"skill_name": "Athena"
},
{
"is_primary": true,
"skill_name": "Databricks"
},
{
"is_primary": true,
"skill_name": "Agile"
},
{
"is_primary": false,
"skill_name": "SAFe Agile"
},
{
"is_primary": false,
"skill_name": "Jira"
},
{
"is_primary": false,
"skill_name": "Git"
},
{
"is_primary": false,
"skill_name": "Jenkins"
},
{
"is_primary": false,
"skill_name": "Linux"
},
{
"is_primary": false,
"skill_name": "AWS CodeCommit"
},
{
"is_primary": false,
"skill_name": "CI/CD"
}
],
"jd_role": {
"display_name": "Senior Lead Engineer",
"rationale": null,
"role_aliases": [
"Lead Engineer",
"Senior Engineer",
"Software Engineer"
],
"role_archetype": "Engineering",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "Collins Aerospace, a Raytheon Technologies",
"last_5_words": "to limitless possibility."
},
"text": "Collins Aerospace, a Raytheon Technologies company, is a leader in technologically advanced and intelligent solutions for the global aerospace and defense industry. Collins Aerospace has the capabilities, comprehensive portfolio and expertise to solve customers\u2019 toughest challenges and to meet the demands of a rapidly evolving global market.\n\nOur Avionics team advances aviation electronics and information management solutions for commercial and military customers across the world. That means we\u2019re helping passengers reach their destination safely. We\u2019re connecting aircraft operators, airports, rail and critical infrastructure with intelligent data service solutions that keep passengers, flight crews and militaries connected and informed. And we\u2019re providing industry-leading fire protection and safety systems that our customers can count on when it matters most. Are you ready to learn from the most knowledgeable experts in the industry, develop the technologies of tomorrow and reach new heights in your career? Join our Avionics team today.\n\nDiversity drives innovation; inclusion drives success. We believe a multitude of approaches and ideas enable us to deliver the best results for our workforce, workplace, and customers. We are committed to fostering a culture where all employees can share their passions and ideas so we can tackle the toughest challenges in our industry and pave new paths to limitless possibility.",
"word_count": 211
},
"certifications": [],
"company_name": "Collins Aerospace",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"Aerospace",
"Defense"
],
"domain": "Aerospace \u0026 Defense"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE - Computer Science / Engineering / MIS (or related)",
"raw": "Bachelor\u0027s Degree (required) and 10+ years\u2019 experience; or Master\u2019s Degree (preferred) and 7+ years\u2019 experience.",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 7,
"raw": "10+ years of technology experience in Software Development Life Cycle"
},
"job_locations": [
{
"aliases": [
"Bengaluru"
],
"city": "Bangalore",
"country": "India",
"state": "Karnataka",
"work_mode": "hybrid"
}
],
"role": "Senior Lead Engineer",
"role_aliases": [
"Lead Engineer",
"Senior Engineer",
"Software Engineer"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 3,
"heading": "Primary Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 You will be responsible",
"last_5_words": "deployment of new data platforms."
},
"text": "\u2022 You will be responsible to understand the client requirement and architect robust data platform on cloud technologies (AWS).\n\u2022 You will be responsible for creating reusable and scalable data pipelines.\n\u2022 You will be responsible for development and deployment of new data platforms.",
"word_count": 36
},
{
"bullet_count": 3,
"heading": "Basic Qualifications",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 10+ years of technology experience",
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},
"text": "\u2022 10+ years of technology experience in Software Development Life Cycle\n\u2022 Above includes 3+ years as Project Lead, Architect\n\u2022 Bachelor\u0027s Degree (required) and 10+ years\u2019 experience; or Master\u2019s Degree (preferred) and 7+ years\u2019 experience. Preferred fields include Computer Science, Engineering, MIS, or related business discipline(s)",
"word_count": 45
},
{
"bullet_count": 18,
"heading": "Preferred Qualifications",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Collaborate with the stakeholders",
"last_5_words": "to the present stakeholders"
},
"text": "\u2022 Collaborate with the stakeholders to gather and prioritize the product requirements\n\u2022 Create and manage product backlog\n\u2022 Strong experience in Agile Methodology (SAFE Agile)\n\u2022 Experience using JIRA or other equivalent tools to create requirements and task management tool\n\u2022 Work closely with the development teams to ensure timely and successful releases and deliverables\n\u2022 Develop detailed user stories, acceptance criteria and wireframes\n\u2022 Act as a bridge between business stakeholders, management, and development teams to facilitate effective communication\n\u2022 Drive the team towards delivering products that meet customer expectations\n\u2022 Work with other development teams to manage dependencies and risks\n\u2022 Good knowledge in Python \u0026 PySpark are preferred\n\u2022 Experience in AWS cloud and AWS services such as S3 Buckets, Lambda, API Gateway, SQS queues, Glue, Kinesis, DynamoDB, Athena etc. (preferred)\n\u2022 Experience with data engineering using Databricks (Mandatory)\n\u2022 Knowledge in DevOps CI/CD tools, such Git, Jenkins, Linux, AWS Code Commit, Build \u0026 Deploy\n\u2022 Knowledge in Security, performance, and Project compliance and processes\n\u2022 Excellent problem-solving skills\n\u2022 Excellent communication skills\n\u2022 Experience working with distributed teams across multiple time zones\n\u2022 Ability to explain a concept with clarity to the present stakeholders",
"word_count": 233
},
{
"bullet_count": 0,
"heading": "Ability",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Ability to provide coaching",
"last_5_words": "coaching and guidance to juniors"
},
"text": "Ability to provide coaching and guidance to juniors",
"word_count": 10
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "7e6d1eb9-d6ff-4628-9e52-707b7980249a",
"stage3_signals": {
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"kra_match_roles": [
{
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{
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"similarity": 0.6337
},
{
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"similarity": 0.5935
},
{
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}
],
"matched_count": null,
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},
{
"display_name": "Fullstack Developer",
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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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"sentence": "Good knowledge in Python \u0026 PySpark are preferred",
"similarity": 0.4798
}
],
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}
],
"skill_match_roles": [
{
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],
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},
{
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},
{
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"Python"
],
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},
{
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"matched_skills": [
"AWS",
"Python"
],
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"score": 0.4,
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"total_count": 5
},
{
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"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"AWS",
"Python"
],
"role_id": 2,
"score": 0.4,
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}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "DOMAIN",
"chosen_role": {
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"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.95,
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},
"confidence": 0.95,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [
"Cloud Data Platform Architecture",
"Data Pipeline Engineering",
"Data Platform Development and Deployment",
"Agile Product Delivery",
"Stakeholder Collaboration",
"DevOps and CI/CD",
"Security and Compliance"
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"matched_kras": [
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"PySpark",
"Databricks",
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"Agile Methodology",
"SAFE Agile",
"Git",
"Jenkins",
"Linux",
"AWS Code Commit",
"Build \u0026 Deploy",
"S3 Buckets",
"Lambda"
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"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Domain=Data Engineering \u0026 Analytics; The JD is centered on cloud data platform architecture, reusable/scalable data pipelines, Databricks, and AWS-based data engineering, which best matches Data Engineer.",
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},
"stage5_updates": {
"centroid_n_after": 241,
"centroid_updated": true,
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"new_kra_attached": null,
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"role_display_name": "Data Engineer",
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},
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"is_primary": false,
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},
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},
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},
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"role_display_name": "Data Engineer",
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},
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"is_primary": false,
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},
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"is_primary": false,
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},
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"is_primary": false,
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},
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"is_primary": false,
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},
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],
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}
}
API 2 — extract-details
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"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
"alias_persisted": false,
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{
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"alias_persisted": false,
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"alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
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"matched_via": "embedding_display_name"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1838,
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"alias_persisted": false,
"existing_alias_id": 868,
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},
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"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
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},
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},
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"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
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],
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"slug": "scala-backend-developer",
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},
{
"display_name": "Web Developer",
"id": 25,
"rationale": null,
"role_archetype": null,
"slug": "web-developer",
"source": "db"
}
]
},
{
"dimension": {
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"display_name": "Cloud Platforms \u0026 Managed Services",
"id": 221,
"rationale": "Operates and integrates vendor-specific cloud compute, storage, and hosting services.",
"slug": "cloud-platforms-managed-services",
"source": "db"
},
"input_skill": "AWS Lambda",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
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"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
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"slug": "go-backend-developer",
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},
{
"display_name": "Node.js Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms \u0026 Services",
"id": 296,
"rationale": "Deploying, configuring, and managing Python backends on major cloud and PaaS offerings.",
"slug": "cloud-platforms-services",
"source": "db"
},
"input_skill": "AWS Lambda",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Python Backend Developer",
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"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
}
]
}
],
"input_skill": "AWS Lambda",
"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": "API Gateway",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
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"skill_nature": "PLATFORM",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
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},
"enrichment": null,
"keep_log": [],
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"merge_log": [],
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"skill_id": "api-gateway",
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"warnings": []
},
"source_tag": "llm",
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},
{
"aliases_in_db": [
{
"alias_text": "SQS",
"alias_type": "CANONICAL",
"id": 3747,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 11,
"display_name": "SQS",
"id": 2442,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CLOUD_SERVICE",
"slug": "sqs",
"sub_category_id": 56,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Asynchronous Messaging and Event Streaming",
"id": 297,
"rationale": "Asynchronous communication patterns and broker technologies used to decouple backend services and move work off the request path. Includes queues, pub/sub, event streams, consumer groups, dead-letter queues, and delivery semantics across systems such as Kafka, RabbitMQ, NATS, SQS/SNS, Pulsar, and ActiveMQ.",
"slug": "asynchronous-messaging-and-event-streaming",
"source": "db"
},
"input_skill": "SQS",
"llm_role": null,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
}
],
"input_skill": "SQS",
"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": "AWS Glue",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
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"skill_nature": "PLATFORM",
"sub_category": "Data Engineering Tools",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
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"merge_log": [],
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"skill_id": "aws-glue",
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"typed": null,
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},
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},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Kinesis",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
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"sub_category": "Message Brokers",
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"volatility": "MEDIUM"
},
"enrichment": null,
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"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Amazon DynamoDB",
"alias_type": "CANONICAL",
"id": 254,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 11,
"display_name": "Amazon DynamoDB",
"id": 93,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CLOUD_SERVICE",
"slug": "amazon-dynamodb",
"sub_category_id": 55,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "NoSQL Databases",
"id": 19,
"rationale": "Models and manages data using non-relational database systems.",
"slug": "nosql-databases",
"source": "db"
},
"input_skill": "DynamoDB",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
}
]
}
],
"input_skill": "DynamoDB",
"matched_via": "embedding_display_name",
"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": "Athena",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Cloud Platforms",
"skill_nature": "PLATFORM",
"sub_category": "Data Engineering Tools",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "athena",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Databricks",
"alias_type": "CANONICAL",
"id": 1838,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 9,
"display_name": "Databricks",
"id": 1202,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "databricks",
"sub_category_id": 911,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "Databricks",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Databricks",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Agile",
"alias_type": "CANONICAL",
"id": 868,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 8,
"display_name": "Agile",
"id": 520,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "agile",
"sub_category_id": 367,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "Agile",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Agile",
"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": "SAFe Agile",
"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,
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"merge_log": [],
"placed": null,
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"skill_id": "safe-agile",
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"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Jira",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Project Management Tools",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
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"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "jira",
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"typed": null,
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},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Git",
"alias_type": "CANONICAL",
"id": 1613,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 13,
"display_name": "Git",
"id": 1002,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "git",
"sub_category_id": 730,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "Git",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Git",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Jenkins",
"alias_type": "CANONICAL",
"id": 544,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 13,
"display_name": "Jenkins",
"id": 283,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "jenkins",
"sub_category_id": 184,
"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": "Jenkins",
"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": "Jenkins",
"llm_role": null,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
}
]
}
],
"input_skill": "Jenkins",
"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": "Linux",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Operating Systems",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "EVERGREEN",
"version_strategy": "UNVERSIONED",
"volatility": "STABLE"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "linux",
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"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "AWS CodeCommit",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Cloud Platforms",
"skill_nature": "PLATFORM",
"sub_category": "Version Control",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
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"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "aws-codecommit",
"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
}
],
"unmatched_skills": [
"API Gateway",
"AWS Glue",
"Kinesis",
"Athena",
"SAFe Agile",
"Jira",
"Linux",
"AWS CodeCommit"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Data Engineer",
"id": 2,
"rationale": "Domain=Data Engineering \u0026 Analytics; The JD is centered on cloud data platform architecture, reusable/scalable data pipelines, Databricks, and AWS-based data engineering, which best matches Data Engineer.",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "AWS",
"tag": "in_db"
},
{
"skill": "Python",
"tag": "in_db"
},
{
"skill": "PySpark",
"tag": "in_db"
},
{
"skill": "S3",
"tag": "in_db"
},
{
"skill": "AWS Lambda",
"tag": "in_db"
},
{
"skill": "API Gateway",
"tag": "new"
},
{
"skill": "SQS",
"tag": "in_db"
},
{
"skill": "AWS Glue",
"tag": "new"
},
{
"skill": "Kinesis",
"tag": "new"
},
{
"skill": "DynamoDB",
"tag": "in_db"
},
{
"skill": "Athena",
"tag": "new"
},
{
"skill": "Databricks",
"tag": "in_db"
},
{
"skill": "Agile",
"tag": "in_db"
},
{
"skill": "SAFe Agile",
"tag": "new"
},
{
"skill": "Jira",
"tag": "new"
},
{
"skill": "Git",
"tag": "in_db"
},
{
"skill": "Jenkins",
"tag": "in_db"
},
{
"skill": "Linux",
"tag": "new"
},
{
"skill": "AWS CodeCommit",
"tag": "new"
},
{
"skill": "CI/CD",
"tag": "in_db"
}
],
"llm_cost_api1_usd": null,
"llm_cost_api2_usd": null,
"llm_cost_api3_usd": null,
"llm_cost_total_usd": null,
"persistence": {
"items": [
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms",
"id": 20,
"rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
"slug": "cloud-platforms",
"source": "db"
},
"dimension_id": 20,
"input_skill": "AWS",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
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{
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{
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{
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{
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{
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}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.