Pipeline run
c4c1b07c-2455-425c-96ec-b69e868d8304
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
Must have relevant experience of at least 4 years in Snowflake. Demonstrate expertise in Snowflake data modelling and ELT/ETL using Snowflake SQL, implementing complex stored procedures and best pract…
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Data Warehouse Engineer
domain · Data Engineering & Analytics CASE DOMAINslug: data-warehouse-engineer · id: 144 · source: db
Domain=Data Engineering & Analytics; The JD is centered on Snowflake development, data warehousing concepts, and modeling/ETL work, which best matches a Snowflake Data Warehouse Engineer role.
Matched skills
Matched dimensions
Matched KRAs
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Role: Snowflake Developer Experience Range: 4+ Years Location : PAN India Mandatory skill: Must have relevant experience of at least 4 years in Snowflake. Demonstrate expertise in Snowflake data modelling and ELT/ETL using Snowflake SQL, implementing complex stored procedures and best practices with data warehouse and ETL concepts Hands-on experience with Snowflake utilities such as Snow SQL, Snow Pipe, Python, Tasks, Streams, Time travel, Optimizer, Metadata Manager, data sharing, and stored procedures. In-depth understanding of Data Warehouse/ODS, ETL concept and modelling structure principles Experience in Data warehousing - OLTP, OLAP, Dimensions, Facts, and Data modelling. Experience gathering and analysing system requirements Good working knowledge of any ETL tool (Informatica or Data stage) Ability to effectively function in a cross team's environment Good to have exposure to AWS / Azure Data ecosystem
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
- Snowflake (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Data Cloud Platform
- Vendor
- Snowflake Inc.
- License
- proprietary
- Year introduced
- 2012
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Snowflake appears frequently in data/analytics job postings and is a standard cloud data warehouse platform alongside BigQuery and Redshift.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 113
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Data Warehouses Catalog dimension db id 22
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Data Warehouses
cloud-data-warehouses
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Programming Languages
- Sub-category
- general
- Skill nature
- LANGUAGE
- 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
- Databases
- 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
- Tools
- Sub-category
- general
- Skill nature
- TOOL
- 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
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
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 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) |
|
Python Programming
python-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Task (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Runtime
- Sub-category
- Task Runtime
- Confidence
- 0.62
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: "Task" as a runtime skill has low JD volume and is usually a generic term, not a named platform; market signals point to niche usage rather than broad hiring demand.
Skill profile (library / DB)
- Skill nature
- RUNTIME
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 67
- Sub-category id
- 2566
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Concurrency and Async Workflows Catalog dimension db id 292
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Python Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Concurrency and Async Workflows
concurrency-and-async-workflows
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
Aliases — catalog
- Streams (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Reactive Stream Concept
- Confidence
- 0.86
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Reactive streams are widely used in JDs for Java, RxJS, and Kafka ecosystems; major vendors and frameworks still document them as a standard async/data-flow pattern rather than a niche tool.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 2226
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Dart Programming Catalog dimension db id 311
Library dimension (catalog)
Roles linked in library: Flutter Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Dart Programming
dart-programming
|
✓ | — | 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
- Databases
- 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
- Databases
- 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
- 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
- Databases
- 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
- Data Engineering Tools
- 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
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- domain modeling (CANONICAL) primary
- Domain Modeling (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Domain Modeling
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Common in software JDs under DDD/business analysis; many roles ask for domain modeling or domain-driven design, and it remains a standard design skill rather than a niche tool.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 2831
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Application Architecture Patterns Catalog dimension db id 293
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Python Backend Developer
-
Service Architecture and Design Patterns Catalog dimension db id 18
Library dimension (catalog)
Roles linked in library: Backend Developer, Java Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, PHP Backend Developer, Ruby Backend Developer, Scala Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Application Architecture Patterns
application-architecture-patterns
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
|
Service Architecture and Design Patterns
service-architecture-and-design-patterns
|
— | — |
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
- Databases
- 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
- Databases
- 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
- Data Engineering Tools
- 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
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Aliases — catalog
- Informatica (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Data Integration Platform
- Vendor
- Informatica
- License
- proprietary
- Year introduced
- 1993
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Informatica appears frequently in enterprise data-integration and ETL job postings, especially alongside cloud migration and MDM roles; it remains a common hiring keyword rather than a sunset technology.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 114
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
ETL and ELT Tooling Catalog dimension db id 24
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
ETL and ELT Tooling
etl-and-elt-tooling
|
✓ | — | Existing dimension (library) · Role↔dimension 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
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- 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 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
- 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 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 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) |
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 |
|---|---|---|---|---|---|---|
| Snowflake | in_db |
Cloud Data Warehouses
cloud-data-warehouses
|
✓ | — | 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 & 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 skipped (dimension not under chosen role) | |
| 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) | |
| Tasks | new |
Concurrency and Async Workflows
concurrency-and-async-workflows
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Streams | in_db |
Dart Programming
dart-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Data Modeling | new |
Application Architecture Patterns
application-architecture-patterns
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Data Modeling | new |
Service Architecture and Design Patterns
service-architecture-and-design-patterns
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Informatica | in_db |
ETL and ELT Tooling
etl-and-elt-tooling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| AWS | in_db |
Cloud Platforms
cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| 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 skipped (dimension not under chosen role) | |
| 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) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Snowflake SQL | type=Programming Languages subtype=general nature=LANGUAGE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Stored Procedures | type=Databases subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | Snow SQL | type=Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Snowpipe | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Time Travel | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Optimizer | type=Databases subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | Data Sharing | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Warehouse | type=Databases subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | ETL | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | ELT | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | OLTP | type=Databases subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | OLAP | type=Databases subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | Dimensions | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | Facts | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | DataStage | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| dimension_skill_link_proposed | Tasks ↔ Concurrency and Async Workflows | |
| dimension_skill_link_proposed | Data Modeling ↔ Application Architecture Patterns | |
| dimension_skill_link_proposed | Data Modeling ↔ Service Architecture and Design Patterns |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [],
"experience": {
"max": null,
"min": 4,
"raw": "4+ Years"
},
"job_locations": [
{
"aliases": [
"PAN India"
],
"city": null,
"country": "India",
"state": null,
"work_mode": null
}
],
"role": "Snowflake Developer",
"role_aliases": [
"Snowflake Engineer",
"Data Engineer",
"Snowflake Specialist"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Mandatory skill",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Must have relevant experience of",
"last_5_words": "AWS / Azure Data ecosystem"
},
"text": "Must have relevant experience of at least 4 years in Snowflake.\nDemonstrate expertise in Snowflake data modelling and ELT/ETL using Snowflake SQL, implementing complex stored procedures and best practices with data warehouse and ETL concepts\nHands-on experience with Snowflake utilities such as Snow SQL, Snow Pipe, Python, Tasks, Streams, Time travel, Optimizer, Metadata Manager, data sharing, and stored procedures.\nIn-depth understanding of Data Warehouse/ODS, ETL concept and modelling structure principles\nExperience in Data warehousing - OLTP, OLAP, Dimensions, Facts, and Data modelling.\nExperience gathering and analysing system requirements\nGood working knowledge of any ETL tool (Informatica or Data stage)\nAbility to effectively function in a cross team\u0027s environment\nGood to have exposure to AWS / Azure Data ecosystem",
"word_count": 134
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Snowflake"
},
{
"is_primary": true,
"skill_name": "Snowflake SQL"
},
{
"is_primary": true,
"skill_name": "Stored Procedures"
},
{
"is_primary": true,
"skill_name": "Snow SQL"
},
{
"is_primary": true,
"skill_name": "Snowpipe"
},
{
"is_primary": true,
"skill_name": "Python"
},
{
"is_primary": true,
"skill_name": "Tasks"
},
{
"is_primary": true,
"skill_name": "Streams"
},
{
"is_primary": true,
"skill_name": "Time Travel"
},
{
"is_primary": true,
"skill_name": "Optimizer"
},
{
"is_primary": true,
"skill_name": "Data Sharing"
},
{
"is_primary": true,
"skill_name": "Data Warehouse"
},
{
"is_primary": true,
"skill_name": "ETL"
},
{
"is_primary": true,
"skill_name": "ELT"
},
{
"is_primary": true,
"skill_name": "Data Modeling"
},
{
"is_primary": true,
"skill_name": "OLTP"
},
{
"is_primary": true,
"skill_name": "OLAP"
},
{
"is_primary": true,
"skill_name": "Dimensions"
},
{
"is_primary": true,
"skill_name": "Facts"
},
{
"is_primary": false,
"skill_name": "Informatica"
},
{
"is_primary": false,
"skill_name": "DataStage"
},
{
"is_primary": false,
"skill_name": "AWS"
},
{
"is_primary": false,
"skill_name": "Azure"
}
],
"jd_role": {
"display_name": "Snowflake Developer",
"rationale": null,
"role_aliases": [
"Snowflake Engineer",
"Data Engineer",
"Snowflake Specialist"
],
"role_archetype": "Data",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [],
"experience": {
"max": null,
"min": 4,
"raw": "4+ Years"
},
"job_locations": [
{
"aliases": [
"PAN India"
],
"city": null,
"country": "India",
"state": null,
"work_mode": null
}
],
"role": "Snowflake Developer",
"role_aliases": [
"Snowflake Engineer",
"Data Engineer",
"Snowflake Specialist"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Mandatory skill",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Must have relevant experience of",
"last_5_words": "AWS / Azure Data ecosystem"
},
"text": "Must have relevant experience of at least 4 years in Snowflake.\nDemonstrate expertise in Snowflake data modelling and ELT/ETL using Snowflake SQL, implementing complex stored procedures and best practices with data warehouse and ETL concepts\nHands-on experience with Snowflake utilities such as Snow SQL, Snow Pipe, Python, Tasks, Streams, Time travel, Optimizer, Metadata Manager, data sharing, and stored procedures.\nIn-depth understanding of Data Warehouse/ODS, ETL concept and modelling structure principles\nExperience in Data warehousing - OLTP, OLAP, Dimensions, Facts, and Data modelling.\nExperience gathering and analysing system requirements\nGood working knowledge of any ETL tool (Informatica or Data stage)\nAbility to effectively function in a cross team\u0027s environment\nGood to have exposure to AWS / Azure Data ecosystem",
"word_count": 134
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "c4c1b07c-2455-425c-96ec-b69e868d8304",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 1.0,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "Data Warehouse Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 144,
"score": 1.0,
"slug": "data-warehouse-engineer",
"total_count": null
}
],
"kra_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": [
{
"kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "In-depth understanding of Data Warehouse/ODS, ETL concept and modelling structure principles",
"similarity": 0.5693
},
{
"kra_text": "Designs dimensional models, star schemas, data vault structures, and curated data mart tables to support BI tools and self-service analytics consumption.",
"sentence": "Demonstrate expertise in Snowflake data modelling and ELT/ETL using Snowflake SQL, implementing complex stored procedures and best practices with data warehouse and ETL concepts",
"similarity": 0.5269
},
{
"kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "Good working knowledge of any ETL tool (Informatica or Data stage)",
"similarity": 0.4896
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.5286,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "Java Backend Developer",
"kra_matches": [
{
"kra_text": "persistence and data modeling",
"sentence": "In-depth understanding of Data Warehouse/ODS, ETL concept and modelling structure principles",
"similarity": 0.5095
},
{
"kra_text": "external system integration",
"sentence": "Experience gathering and analysing system requirements",
"similarity": 0.4457
},
{
"kra_text": "persistence and data modeling",
"sentence": "Demonstrate expertise in Snowflake data modelling and ELT/ETL using Snowflake SQL, implementing complex stored procedures and best practices with data warehouse and ETL concepts",
"similarity": 0.411
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 79,
"score": 0.4554,
"slug": "java-backend-developer",
"total_count": null
},
{
"display_name": "Pega Developer",
"kra_matches": [
{
"kra_text": "Requirements analysis and process translation",
"sentence": "Experience gathering and analysing system requirements",
"similarity": 0.6208
},
{
"kra_text": "Requirements analysis and process translation",
"sentence": "In-depth understanding of Data Warehouse/ODS, ETL concept and modelling structure principles",
"similarity": 0.3661
},
{
"kra_text": "external system integration implementation",
"sentence": "Ability to effectively function in a cross team\u0027s environment",
"similarity": 0.3534
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 24,
"score": 0.4468,
"slug": "pega-developer",
"total_count": null
},
{
"display_name": "Flutter Developer",
"kra_matches": [
{
"kra_text": "translate product and design requirements",
"sentence": "Experience gathering and analysing system requirements",
"similarity": 0.4905
},
{
"kra_text": "integrate external APIs and data sources",
"sentence": "Good to have exposure to AWS / Azure Data ecosystem",
"similarity": 0.4007
},
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Ability to effectively function in a cross team\u0027s environment",
"similarity": 0.3988
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 74,
"score": 0.43,
"slug": "flutter-developer",
"total_count": null
},
{
"display_name": "Node.js Backend Developer",
"kra_matches": [
{
"kra_text": "data modeling and persistence access",
"sentence": "In-depth understanding of Data Warehouse/ODS, ETL concept and modelling structure principles",
"similarity": 0.4466
},
{
"kra_text": "external system integration",
"sentence": "Experience gathering and analysing system requirements",
"similarity": 0.4457
},
{
"kra_text": "external system integration",
"sentence": "Ability to effectively function in a cross team\u0027s environment",
"similarity": 0.381
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 82,
"score": 0.4244,
"slug": "node-backend-developer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"Python",
"Snowflake"
],
"role_id": 2,
"score": 0.1053,
"slug": "data-engineer",
"total_count": 19
},
{
"display_name": "ML Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Python"
],
"role_id": 3,
"score": 0.0526,
"slug": "ml-engineer",
"total_count": 19
},
{
"display_name": "Cyber Security Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Python"
],
"role_id": 5,
"score": 0.0526,
"slug": "cybersecurity-engineer",
"total_count": 19
},
{
"display_name": "AR/VR Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Python"
],
"role_id": 8,
"score": 0.0526,
"slug": "ar-vr-engineer",
"total_count": 19
},
{
"display_name": "Backend Developer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Python"
],
"role_id": 1,
"score": 0.0526,
"slug": "backend-engineer",
"total_count": 19
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "DOMAIN",
"chosen_role": {
"display_name": "Data Warehouse Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 144,
"score": 0.95,
"slug": "data-warehouse-engineer",
"total_count": null
},
"confidence": 0.95,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [
"Snowflake data modeling",
"Data warehouse engineering",
"ELT/ETL development",
"Stored procedure implementation",
"Data warehouse and ODS concepts",
"OLTP/OLAP modeling",
"Requirements analysis",
"Cross-team collaboration",
"Cloud data ecosystem exposure"
],
"matched_kras": [
"Demonstrate expertise in Snowflake data modelling and ELT/ETL",
"Implementing complex stored procedures and best practices",
"Hands-on experience with Snowflake utilities",
"Understanding of Data Warehouse/ODS, ETL concept and modelling",
"Experience in Data warehousing - OLTP, OLAP, Dimensions, Facts",
"Experience gathering and analysing system requirements",
"Function in a cross team\u0027s environment"
],
"matched_skills": [
"Snowflake",
"Snowflake SQL",
"Snow SQL",
"Snow Pipe",
"Python",
"Tasks",
"Streams",
"Time travel",
"Optimizer",
"Metadata Manager",
"data sharing",
"stored procedures",
"Informatica",
"Data stage",
"AWS",
"Azure"
],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Domain=Data Engineering \u0026 Analytics; The JD is centered on Snowflake development, data warehousing concepts, and modeling/ETL work, which best matches a Snowflake Data Warehouse Engineer role.",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 18,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": {
"best_kra_similarity": 0.0,
"queue_id": 1618,
"r_and_r_preview": "Must have relevant experience of at least 4 years in Snowflake.\nDemonstrate expertise in Snowflake data modelling and ELT/ETL using Snowflake SQL, implementing complex stored procedures and best pract",
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"status": "pending"
},
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 21562,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "Snowflake SQL",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21563,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "Stored Procedures",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21564,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "Snow SQL",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21565,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "Snowpipe",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21566,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "Tasks",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21567,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "Time Travel",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21568,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "Optimizer",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21569,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "Data Sharing",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21570,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "Data Warehouse",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21571,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "ETL",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21572,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "ELT",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21573,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "Data Modeling",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21574,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "OLTP",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21575,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "OLAP",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21576,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "Dimensions",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 21577,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "Facts",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 21578,
"role_display_name": "Data Warehouse Engineer",
"role_slug": "data-warehouse-engineer",
"skill_name": "DataStage",
"status": "pending"
}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{
"alias_matches": [
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 299,
"existing_alias_text": "Snowflake",
"input_term": "Snowflake",
"matched_canonical": {
"category_id": 9,
"display_name": "Snowflake",
"id": 105,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "snowflake",
"sub_category_id": 113,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 67,
"existing_alias_text": "Python",
"input_term": "Python",
"matched_canonical": {
"category_id": 6,
"display_name": "Python",
"id": 5,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "python",
"sub_category_id": 96,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
"alias_persisted": false,
"existing_alias_id": 4813,
"existing_alias_text": "Task",
"input_term": "Tasks",
"matched_canonical": {
"category_id": 67,
"display_name": "Task",
"id": 3264,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "RUNTIME",
"slug": "task",
"sub_category_id": 2566,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "embedding_alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 4368,
"existing_alias_text": "Streams",
"input_term": "Streams",
"matched_canonical": {
"category_id": 2,
"display_name": "Streams",
"id": 2913,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "streams",
"sub_category_id": 2226,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
"alias_persisted": false,
"existing_alias_id": 5644,
"existing_alias_text": "Domain Modeling",
"input_term": "Data Modeling",
"matched_canonical": {
"category_id": 8,
"display_name": "domain modeling",
"id": 2379,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "domain-modeling",
"sub_category_id": 2831,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "embedding_alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 311,
"existing_alias_text": "Informatica",
"input_term": "Informatica",
"matched_canonical": {
"category_id": 9,
"display_name": "Informatica",
"id": 117,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "informatica",
"sub_category_id": 114,
"typical_lifespan": "EVERGREEN",
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},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 406,
"existing_alias_text": "AWS",
"input_term": "AWS",
"matched_canonical": {
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"display_name": "AWS",
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"is_also_category": false,
"is_extractable": true,
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"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms \u0026 Managed Services",
"id": 221,
"rationale": "Operates and integrates vendor-specific cloud compute, storage, and hosting services.",
"slug": "cloud-platforms-managed-services",
"source": "db"
},
"input_skill": "Azure",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms for AI Deployment",
"id": 211,
"rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
"slug": "cloud-platforms-for-ai-deployment",
"source": "db"
},
"input_skill": "Azure",
"llm_role": null,
"roles_from_db": [
{
"display_name": "AI Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Provider Platforms",
"id": 131,
"rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
"slug": "cloud-provider-platforms",
"source": "db"
},
"input_skill": "Azure",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
},
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Posture Tools",
"id": 64,
"rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
"slug": "cloud-security-posture-tools",
"source": "db"
},
"input_skill": "Azure",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Vendor Product Families",
"id": 477,
"rationale": "Coordinate usage, licensing, and architecture decisions for major vendor software and cloud product families.",
"slug": "vendor-product-families",
"source": "db"
},
"input_skill": "Azure",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
}
]
}
],
"input_skill": "Azure",
"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": [
"Snowflake SQL",
"Stored Procedures",
"Snow SQL",
"Snowpipe",
"Time Travel",
"Optimizer",
"Data Sharing",
"Data Warehouse",
"ETL",
"ELT",
"OLTP",
"OLAP",
"Dimensions",
"Facts",
"DataStage"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Data Warehouse Engineer",
"id": 144,
"rationale": "Domain=Data Engineering \u0026 Analytics; The JD is centered on Snowflake development, data warehousing concepts, and modeling/ETL work, which best matches a Snowflake Data Warehouse Engineer role.",
"role_archetype": null,
"slug": "data-warehouse-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Snowflake",
"tag": "in_db"
},
{
"skill": "Snowflake SQL",
"tag": "new"
},
{
"skill": "Stored Procedures",
"tag": "new"
},
{
"skill": "Snow SQL",
"tag": "new"
},
{
"skill": "Snowpipe",
"tag": "new"
},
{
"skill": "Python",
"tag": "in_db"
},
{
"skill": "Tasks",
"tag": "in_db"
},
{
"skill": "Streams",
"tag": "in_db"
},
{
"skill": "Time Travel",
"tag": "new"
},
{
"skill": "Optimizer",
"tag": "new"
},
{
"skill": "Data Sharing",
"tag": "new"
},
{
"skill": "Data Warehouse",
"tag": "new"
},
{
"skill": "ETL",
"tag": "new"
},
{
"skill": "ELT",
"tag": "new"
},
{
"skill": "Data Modeling",
"tag": "in_db"
},
{
"skill": "OLTP",
"tag": "new"
},
{
"skill": "OLAP",
"tag": "new"
},
{
"skill": "Dimensions",
"tag": "new"
},
{
"skill": "Facts",
"tag": "new"
},
{
"skill": "Informatica",
"tag": "in_db"
},
{
"skill": "DataStage",
"tag": "new"
},
{
"skill": "AWS",
"tag": "in_db"
},
{
"skill": "Azure",
"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": 144,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Data Warehouses",
"id": 22,
"rationale": "Managed analytical storage and compute platforms used for curated datasets, reporting, and downstream analytics. These systems are central to data modeling, performance tuning, and cost-aware query design.",
"slug": "cloud-data-warehouses",
"source": "db"
},
"dimension_id": 22,
"input_skill": "Snowflake",
"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": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 105,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 144,
"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": 144,
"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": 144,
"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": 144,
"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": 144,
"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": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"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": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 144,
"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": 144,
"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": 144,
"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": 144,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Concurrency and Async Workflows",
"id": 292,
"rationale": "Programming techniques for handling concurrent requests, asynchronous I/O, and coordination of background execution in Python services. This cluster is coherent because backend developers must safely manage throughput and responsiveness.",
"slug": "concurrency-and-async-workflows",
"source": "db"
},
"dimension_id": 292,
"input_skill": "Tasks",
"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": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": null,
"skill_tag": "new",
"skipped_reason": "skill_not_in_db_v3_proposed"
},
{
"chosen_role_id": 144,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Dart Programming",
"id": 311,
"rationale": "Core implementation language used to build Flutter app logic, UI composition, and client-side feature code. This is the primary coding surface for shared cross-platform app development.",
"slug": "dart-programming",
"source": "db"
},
"dimension_id": 311,
"input_skill": "Streams",
"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": "Flutter Developer",
"id": 74,
"rationale": null,
"role_archetype": "Engineering",
"slug": "flutter-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 2913,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 144,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Application Architecture Patterns",
"id": 293,
"rationale": "Structural patterns for organizing Python backend code into maintainable modules, layers, and feature boundaries. This is a coherent cluster because senior backend developers are expected to refactor and shape service internals over time.",
"slug": "application-architecture-patterns",
"source": "db"
},
"dimension_id": 293,
"input_skill": "Data Modeling",
"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": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": false,
"skill_id": null,
"skill_tag": "new",
"skipped_reason": "skill_not_in_db_v3_proposed"
},
{
"chosen_role_id": 144,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Service Architecture and Design Patterns",
"id": 18,
"rationale": "Reusable backend design patterns used to structure service code and boundaries. Covers layering, dependency management, domain modeling, and maintainable service organization.",
"slug": "service-architecture-and-design-patterns",
"source": "db"
},
"dimension_id": 18,
"input_skill": "Data Modeling",
"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": "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": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
},
{
"display_name": "Ruby Backend Developer",
"id": 85,
"rationale": null,
"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
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