Pipeline run
8058b9a4-146f-4151-b889-0a38ade4c229
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
Captured for admin review
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Data Engineer
CASE Aslug: data-engineer · id: 2 · source: db
Exact alias hit on data-engineer (1.0) — no other alias at this confidence; skill_top data-engineer 0.25 does not contradict
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Job Reference # 281735BR Job Type Full Time Your role You will be a member of the Artificial Intelligence, Data, and Analytics (ADA) Crew. Together with your colleagues you will contribute to building and maintaining a robust and secure self-service HR data analytics and data science platform. You will contribute to our most ambitious and critical technology projects as we migrate our applications onto the Azure cloud platform. We’re looking for a Data Engineer to: • Design and develop new cloud-based data analytics products and services for UBS HR • ensure the quality, security, reliability, and compliance of our solutions by applying our digital principles and implementing both functional and non-functional requirements. • build observability into our solutions to monitor production health, help to resolve incidents, and remediate the root cause of risks and issues. • migrate legacy data warehouse applications onto Azure, build new data pipelines and data marts, design data models and create data visualizations • continuously up-skill, learn new technologies and practices, reuse strategic platforms and standards, evaluate options, and make decisions with long-term sustainability in mind. Your team You’ll be working in an agile and autonomous team in the HR ADA Crew in Pune. We are a global organization that values diversity, collaboration, engineering & digital culture, and innovation. You will join the UBS Certified Engineer program which offers many learning opportunities. This is one of many strategic initiatives to drive engineering excellence. Your expertise • high proficiency and 8+ years of experience in designing/developing data analytics and data warehouse solutions with Azure Data Factory (ADF) and Azure Data Bricks. • a strong knowledge of one or more of Oracle and PL/SQL, Postgres, Informatica ETL, Tableau, Business Objects, PowerBI, Azure Synapse Analytics. • Understanding of full stack (backend, frontend, network, OS, middleware), Azure Technology stack preferred • a proven track of work experience in cloud deployments (MS Azure preferred) in an agile SDLC environment, leveraging modern programming languages, DevOps, SQL and noSQL databases, and test-driven development. • prior strong working experience in designing, developing, maintaining universes and web intelligence reports in SAP Business Objects and/or Tableau and SQL. • ability to assist users with complex scenarios in SAP BO and Tableau Desktop/server, guiding them to resolve their questions. Conduct performance tuning for SAP BO, Tableau SQL views etc. • you hold a relevant bachelor’s degree or equivalent. You are a strong communicator, fluent in English, from making presentations to technical writing. About Us UBS is the world’s largest and the only truly global wealth manager. We operate through four business divisions: Global Wealth Management, Personal & Corporate Banking, Asset Management and the Investment Bank. Our global reach and the breadth of our expertise set us apart from our competitors.. We have a presence in all major financial centers in more than 50 countries. How We Hire This role requires an assessment on application. Learn more about how we hire: www.ubs.com/global/en/careers/experienced-professionals.html Join us At UBS, we embrace flexible ways of working when the role permits. We offer different working arrangements like part-time, job-sharing and hybrid (office and home) working. Our purpose-led culture and global infrastructure help us connect, collaborate, and work together in agile ways to meet all our business needs. From gaining new experiences in different roles to acquiring fresh knowledge and skills, we know that great work is never done alone. We know that it's our people, with their unique backgrounds, skills, experience levels and interests, who drive our ongoing success. Together we’re more than ourselves. Ready to be part of #teamUBS and make an impact? Disclaimer / Policy Statements UBS is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills and experiences within our workforce. Your Career Comeback We are open to applications from career returners. Find out more about our program on ubs.com/careercomeback.
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
- 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
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
|
Cloud Platforms & Managed Services
cloud-platforms-managed-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Databases
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- PL/SQL (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Procedural Sql Language
- Vendor
- Oracle Corporation
- License
- proprietary
- Year introduced
- 1990
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: PL/SQL appears frequently in Oracle-focused job postings and remains a standard skill for Oracle database development and maintenance; it is not sunset or replaced by a newer successor.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 1173
- 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
- PostgreSQL (CANONICAL) primary
- PG 13 (VERSION)
- PG 14 (VERSION)
- PG 15 (VERSION)
- PG 16 (VERSION)
- PostgreSQL 13 (VERSION)
- PostgreSQL 14 (VERSION)
- PostgreSQL 15 (VERSION)
- PostgreSQL 16 (VERSION)
- Postgres 13 (VERSION)
- Postgres 14 (VERSION)
- Postgres 15 (VERSION)
- Postgres 16 (VERSION)
- pg10 (VERSION)
- pg11 (VERSION)
- pg12 (VERSION)
- pg13 (VERSION)
- pg14 (VERSION)
- pg15 (VERSION)
- pg16 (VERSION)
- postgres (VERSION)
- postgresql 10 (VERSION)
- postgresql 11 (VERSION)
- postgresql 12 (VERSION)
- postgresql 13 (VERSION)
- postgresql 14 (VERSION)
- postgresql 15 (VERSION)
- postgresql 16 (VERSION)
- postgresql-16 (VERSION)
- postgresql10 (VERSION)
- postgresql11 (VERSION)
- postgresql12 (VERSION)
- postgresql13 (VERSION)
- postgresql14 (VERSION)
- postgresql15 (VERSION)
- postgresql16 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Relational Database
- Vendor
- PostgreSQL Global Development Group
- License
- other_open
- Year introduced
- 1996
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: PostgreSQL appears in a large share of backend/data engineering job postings and is a default managed option across AWS RDS, GCP Cloud SQL, and Azure Database, indicating broad hiring-pipeline adoption.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 29
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Relational Data Modeling Catalog dimension db id 216
Library dimension (catalog)
Roles linked in library: Fullstack Developer, Fullstack Developer, PHP Backend Developer
-
Relational Database Design Catalog dimension db id 4
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer
-
Relational Database Usage Catalog dimension db id 371
Library dimension (catalog)
Roles linked in library: Go Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Relational Data Modeling
relational-data-modeling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Relational Database Usage
relational-database-usage
|
✓ | — | 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
- Tableau (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Bi Analytics Platform
- Vendor
- Tableau Software
- License
- proprietary
- Year introduced
- 2003
- Confidence
- 0.96
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Tableau appears frequently in BI/data analyst job descriptions and remains a standard enterprise analytics platform with strong vendor support and broad adoption.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 111
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
BI and Visualization Tools Catalog dimension db id 31
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
BI and Visualization Tools
bi-and-visualization-tools
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Business Intelligence Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Power BI (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Bi Analytics Platform
- Vendor
- Microsoft
- License
- proprietary
- Year introduced
- 2015
- Confidence
- 0.96
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Power BI appears frequently in BI/data analyst job descriptions and is a standard Microsoft analytics platform in enterprise stacks, with strong vendor support and broad adoption.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 111
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
BI and Visualization Tools Catalog dimension db id 31
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
BI and Visualization Tools
bi-and-visualization-tools
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- Azure Synapse Analytics (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Service
- Sub-category
- Analytics Service
- Vendor
- Microsoft
- License
- proprietary
- Year introduced
- 2019
- Confidence
- 0.95
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Common in cloud data-platform JDs and Microsoft’s Azure analytics stack; often listed alongside Databricks/ADF for warehousing and ETL, indicating broad hiring demand.
Skill profile (library / DB)
- Skill nature
- CLOUD_SERVICE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 11
- Sub-category id
- 117
- 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 saved |
Aliases — catalog
- SQL (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Query Language
- Vendor
- ANSI
- License
- unknown
- Year introduced
- 1974
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: SQL appears in a large share of data, backend, and analytics job descriptions and remains the default query language for PostgreSQL, MySQL, and cloud warehouses like Snowflake/BigQuery.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 97
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Pega Programming Languages & DSLs Catalog dimension db id 267
Library dimension (catalog)
Roles linked in library: Pega Developer
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | 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 |
Aliases — catalog
- NoSQL (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Database Paradigm
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: NoSQL is broadly listed in job descriptions across backend/data roles, with MongoDB, DynamoDB, and Cassandra appearing as common market signals; it remains a hiring-pipeline staple rather than a niche or sunset tech.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1019
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
NoSQL Databases Catalog dimension db id 19
Library dimension (catalog)
Roles linked in library: Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
NoSQL Databases
nosql-databases
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
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) |
Aliases — catalog
- SDLC (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Software Development Lifecycle
- Confidence
- 0.88
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: SDLC is a standard hiring-pipeline term across software roles; job postings commonly require experience with SDLC phases, Agile/Waterfall, and release processes rather than treating it as niche tooling.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 1179
- 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
- DevOps (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Devops Methodology
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: DevOps appears in a large share of software and platform engineering job descriptions, often alongside CI/CD, Kubernetes, and cloud tooling; it is a standard hiring-pipeline keyword rather than a niche specialty.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 922
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
CI/CD Pipeline Platforms Catalog dimension db id 150
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Deployment and Release Patterns Catalog dimension db id 140
Library dimension (catalog)
Roles linked in library: Cloud Architect
-
Infrastructure as Code Catalog dimension db id 132
Library dimension (catalog)
Roles linked in library: Cloud Architect, DevOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Deployment and Release Patterns
deployment-and-release-patterns
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Infrastructure as Code
infrastructure-as-code
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Practices
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Business Intelligence Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Tableau (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Bi Analytics Platform
- Vendor
- Tableau Software
- License
- proprietary
- Year introduced
- 2003
- Confidence
- 0.96
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Tableau appears frequently in BI/data analyst job descriptions and remains a standard enterprise analytics platform with strong vendor support and broad adoption.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 111
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
BI and Visualization Tools Catalog dimension db id 31
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
BI and Visualization Tools
bi-and-visualization-tools
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
Aliases — catalog
- Tableau (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Bi Analytics Platform
- Vendor
- Tableau Software
- License
- proprietary
- Year introduced
- 2003
- Confidence
- 0.96
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Tableau appears frequently in BI/data analyst job descriptions and remains a standard enterprise analytics platform with strong vendor support and broad adoption.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 111
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
BI and Visualization Tools Catalog dimension db id 31
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
BI and Visualization Tools
bi-and-visualization-tools
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
All API 3 persistence rows
Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.
| Skill | Tag | Dimension | Skill↔dim | Role↔dim | Outcome | Notes |
|---|---|---|---|---|---|---|
| Azure | in_db |
Cloud Platforms
cloud-platforms
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Azure | in_db |
Cloud Platforms & Managed Services
cloud-platforms-managed-services
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Platforms for AI Deployment
cloud-platforms-for-ai-deployment
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Provider Platforms
cloud-provider-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Azure | in_db |
Cloud Security Posture Tools
cloud-security-posture-tools
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| PL/SQL | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| PostgreSQL | in_db |
Relational Data Modeling
relational-data-modeling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| PostgreSQL | in_db |
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| PostgreSQL | in_db |
Relational Database Usage
relational-database-usage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Tableau | in_db |
BI and Visualization Tools
bi-and-visualization-tools
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Power BI | in_db |
BI and Visualization Tools
bi-and-visualization-tools
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Azure Synapse Analytics | in_db |
Cloud Data Warehouses
cloud-data-warehouses
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| SQL | in_db |
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| SQL | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| NoSQL | in_db |
NoSQL Databases
nosql-databases
|
✓ | — | 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) | |
| SDLC | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
Deployment and Release Patterns
deployment-and-release-patterns
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| DevOps | in_db |
Infrastructure as Code
infrastructure-as-code
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Tableau Desktop | new |
BI and Visualization Tools
bi-and-visualization-tools
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| Tableau Server | new |
BI and Visualization Tools
bi-and-visualization-tools
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Azure Data Factory | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Azure Databricks | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Oracle | type=Databases subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Informatica ETL | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Business Objects | type=Business Intelligence Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Test-Driven Development | type=Practices subtype=general nature=PRACTICE lifespan=EVERGREEN | |
| canonical_skill_proposed | SAP Business Objects | type=Business Intelligence Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| dimension_skill_link_proposed | Tableau Desktop ↔ BI and Visualization Tools | |
| role_dimension_link_proposed | Data Engineer ↔ BI and Visualization Tools | |
| dimension_skill_link_proposed | Tableau Server ↔ BI and Visualization Tools | |
| role_dimension_link_proposed | Data Engineer ↔ BI and Visualization Tools |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "UBS is the world\u2019s largest",
"last_5_words": "in more than 50 countries."
},
"text": "UBS is the world\u2019s largest and the only truly global wealth manager. We operate through four business divisions: Global Wealth Management, Personal \u0026 Corporate Banking, Asset Management and the Investment Bank. Our global reach and the breadth of our expertise set us apart from our competitors.. We have a presence in all major financial centers in more than 50 countries.",
"word_count": 64
},
"certifications": [],
"company_name": "UBS",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"FinTech",
"Wealth Management"
],
"domain": "Financial Services"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "Bachelor\u0027s - Relevant",
"raw": "you hold a relevant bachelor\u2019s degree or equivalent",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 8,
"raw": "8+ years of experience"
},
"job_locations": [
{
"aliases": [
"Pune, Maharashtra"
],
"city": "Pune",
"country": "India",
"state": null,
"work_mode": "hybrid"
}
],
"role": "Data Engineer",
"role_aliases": [
"Data Engineer",
"Data Analytics Engineer",
"Cloud Data Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Your role",
"heading_was_present": true,
"source_marker": {
"first_5_words": "You will be a member",
"last_5_words": "onto the Azure cloud platform."
},
"text": "You will be a member of the Artificial Intelligence, Data, and Analytics (ADA) Crew. Together with your colleagues you will contribute to building and maintaining a robust and secure self-service HR data analytics and data science platform. You will contribute to our most ambitious and critical technology projects as we migrate our applications onto the Azure cloud platform.",
"word_count": 51
},
{
"bullet_count": 5,
"heading": "We\u2019re looking for a Data Engineer to:",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Design and develop new",
"last_5_words": "with long-term sustainability in mind."
},
"text": "\u2022 Design and develop new cloud-based data analytics products and services for UBS HR\n\u2022 ensure the quality, security, reliability, and compliance of our solutions by applying our digital principles and implementing both functional and non-functional requirements.\n\u2022 build observability into our solutions to monitor production health, help to resolve incidents, and remediate the root cause of risks and issues.\n\u2022 migrate legacy data warehouse applications onto Azure, build new data pipelines and data marts, design data models and create data visualizations\n\u2022 continuously up-skill, learn new technologies and practices, reuse strategic platforms and standards, evaluate options, and make decisions with long-term sustainability in mind.",
"word_count": 104
},
{
"bullet_count": 7,
"heading": "Your expertise",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 high proficiency and 8+",
"last_5_words": "to technical writing."
},
"text": "\u2022 high proficiency and 8+ years of experience in designing/developing data analytics and data warehouse solutions with Azure Data Factory (ADF) and Azure Data Bricks.\n\u2022 a strong knowledge of one or more of Oracle and PL/SQL, Postgres, Informatica ETL, Tableau, Business Objects, PowerBI, Azure Synapse Analytics.\n\u2022 Understanding of full stack (backend, frontend, network, OS, middleware), Azure Technology stack preferred\n\u2022 a proven track of work experience in cloud deployments (MS Azure preferred) in an agile SDLC environment, leveraging modern programming languages, DevOps, SQL and noSQL databases, and test-driven development.\n\u2022 prior strong working experience in designing, developing, maintaining universes and web intelligence reports in SAP Business Objects and/or Tableau and SQL.\n\u2022 ability to assist users with complex scenarios in SAP BO and Tableau Desktop/server, guiding them to resolve their questions. Conduct performance tuning for SAP BO, Tableau SQL views etc.\n\u2022 you hold a relevant bachelor\u2019s degree or equivalent. You are a strong communicator, fluent in English, from making presentations to technical writing.",
"word_count": 174
}
],
"urls": [
{
"type": "careers",
"url": "www.ubs.com/global/en/careers/experienced-professionals.html"
},
{
"type": "other",
"url": "ubs.com/careercomeback"
}
]
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Azure"
},
{
"is_primary": true,
"skill_name": "Azure Data Factory"
},
{
"is_primary": true,
"skill_name": "Azure Databricks"
},
{
"is_primary": true,
"skill_name": "Oracle"
},
{
"is_primary": true,
"skill_name": "PL/SQL"
},
{
"is_primary": true,
"skill_name": "PostgreSQL"
},
{
"is_primary": true,
"skill_name": "Informatica ETL"
},
{
"is_primary": true,
"skill_name": "Tableau"
},
{
"is_primary": true,
"skill_name": "Business Objects"
},
{
"is_primary": true,
"skill_name": "Power BI"
},
{
"is_primary": true,
"skill_name": "Azure Synapse Analytics"
},
{
"is_primary": true,
"skill_name": "SQL"
},
{
"is_primary": true,
"skill_name": "NoSQL"
},
{
"is_primary": true,
"skill_name": "Agile"
},
{
"is_primary": true,
"skill_name": "SDLC"
},
{
"is_primary": true,
"skill_name": "DevOps"
},
{
"is_primary": true,
"skill_name": "Test-Driven Development"
},
{
"is_primary": true,
"skill_name": "SAP Business Objects"
},
{
"is_primary": true,
"skill_name": "Tableau Desktop"
},
{
"is_primary": true,
"skill_name": "Tableau Server"
}
],
"jd_role": {
"display_name": "Data Engineer",
"rationale": null,
"role_aliases": [
"Data Engineer",
"Data Analytics Engineer",
"Cloud Data Engineer"
],
"role_archetype": "Data",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "UBS is the world\u2019s largest",
"last_5_words": "in more than 50 countries."
},
"text": "UBS is the world\u2019s largest and the only truly global wealth manager. We operate through four business divisions: Global Wealth Management, Personal \u0026 Corporate Banking, Asset Management and the Investment Bank. Our global reach and the breadth of our expertise set us apart from our competitors.. We have a presence in all major financial centers in more than 50 countries.",
"word_count": 64
},
"certifications": [],
"company_name": "UBS",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"FinTech",
"Wealth Management"
],
"domain": "Financial Services"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "Bachelor\u0027s - Relevant",
"raw": "you hold a relevant bachelor\u2019s degree or equivalent",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 8,
"raw": "8+ years of experience"
},
"job_locations": [
{
"aliases": [
"Pune, Maharashtra"
],
"city": "Pune",
"country": "India",
"state": null,
"work_mode": "hybrid"
}
],
"role": "Data Engineer",
"role_aliases": [
"Data Engineer",
"Data Analytics Engineer",
"Cloud Data Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Your role",
"heading_was_present": true,
"source_marker": {
"first_5_words": "You will be a member",
"last_5_words": "onto the Azure cloud platform."
},
"text": "You will be a member of the Artificial Intelligence, Data, and Analytics (ADA) Crew. Together with your colleagues you will contribute to building and maintaining a robust and secure self-service HR data analytics and data science platform. You will contribute to our most ambitious and critical technology projects as we migrate our applications onto the Azure cloud platform.",
"word_count": 51
},
{
"bullet_count": 5,
"heading": "We\u2019re looking for a Data Engineer to:",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Design and develop new",
"last_5_words": "with long-term sustainability in mind."
},
"text": "\u2022 Design and develop new cloud-based data analytics products and services for UBS HR\n\u2022 ensure the quality, security, reliability, and compliance of our solutions by applying our digital principles and implementing both functional and non-functional requirements.\n\u2022 build observability into our solutions to monitor production health, help to resolve incidents, and remediate the root cause of risks and issues.\n\u2022 migrate legacy data warehouse applications onto Azure, build new data pipelines and data marts, design data models and create data visualizations\n\u2022 continuously up-skill, learn new technologies and practices, reuse strategic platforms and standards, evaluate options, and make decisions with long-term sustainability in mind.",
"word_count": 104
},
{
"bullet_count": 7,
"heading": "Your expertise",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 high proficiency and 8+",
"last_5_words": "to technical writing."
},
"text": "\u2022 high proficiency and 8+ years of experience in designing/developing data analytics and data warehouse solutions with Azure Data Factory (ADF) and Azure Data Bricks.\n\u2022 a strong knowledge of one or more of Oracle and PL/SQL, Postgres, Informatica ETL, Tableau, Business Objects, PowerBI, Azure Synapse Analytics.\n\u2022 Understanding of full stack (backend, frontend, network, OS, middleware), Azure Technology stack preferred\n\u2022 a proven track of work experience in cloud deployments (MS Azure preferred) in an agile SDLC environment, leveraging modern programming languages, DevOps, SQL and noSQL databases, and test-driven development.\n\u2022 prior strong working experience in designing, developing, maintaining universes and web intelligence reports in SAP Business Objects and/or Tableau and SQL.\n\u2022 ability to assist users with complex scenarios in SAP BO and Tableau Desktop/server, guiding them to resolve their questions. Conduct performance tuning for SAP BO, Tableau SQL views etc.\n\u2022 you hold a relevant bachelor\u2019s degree or equivalent. You are a strong communicator, fluent in English, from making presentations to technical writing.",
"word_count": 174
}
],
"urls": [
{
"type": "careers",
"url": "www.ubs.com/global/en/careers/experienced-professionals.html"
},
{
"type": "other",
"url": "ubs.com/careercomeback"
}
]
},
"rejected": false,
"rejection_reason": null,
"run_id": "8058b9a4-146f-4151-b889-0a38ade4c229",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 1.0,
"slug": "data-engineer",
"total_count": null
}
],
"kra_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": [
{
"kra_text": "Designs dimensional models, star schemas, data vault structures, and curated data mart tables to support BI tools and self-service analytics consumption.",
"sentence": "prior strong working experience in designing, developing, maintaining universes and web intelligence reports in SAP Business Objects and/or Tableau and SQL.",
"similarity": 0.5651
},
{
"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": "migrate legacy data warehouse applications onto Azure, build new data pipelines and data marts, design data models and create data visualizations",
"similarity": 0.5556
},
{
"kra_text": "Monitors pipeline health, SLA breach alerts, and job failure notifications, and performs root cause analysis for data pipeline incidents.",
"sentence": "build observability into our solutions to monitor production health, help to resolve incidents, and remediate the root cause of risks and issues.",
"similarity": 0.5134
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.5447,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "Cloud Architect",
"kra_matches": [
{
"kra_text": "Defines cloud adoption roadmaps, lift-and-shift vs. refactor migration strategies, and landing zone architectures for workloads moving to AWS, Azure, or GCP.",
"sentence": "migrate legacy data warehouse applications onto Azure, build new data pipelines and data marts, design data models and create data visualizations",
"similarity": 0.5481
},
{
"kra_text": "Conducts architecture reviews, approves technical design documents, and guides engineering teams through cloud migration and modernization projects.",
"sentence": "a proven track of work experience in cloud deployments (MS Azure preferred) in an agile SDLC environment, leveraging modern programming languages, DevOps, SQL and noSQL databases, and test-driven development.",
"similarity": 0.5309
},
{
"kra_text": "Defines cloud adoption roadmaps, lift-and-shift vs. refactor migration strategies, and landing zone architectures for workloads moving to AWS, Azure, or GCP.",
"sentence": "You will contribute to our most ambitious and critical technology projects as we migrate our applications onto the Azure cloud platform.",
"similarity": 0.503
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 9,
"score": 0.5273,
"slug": "cloud-architect",
"total_count": null
},
{
"display_name": "DevOps Engineer",
"kra_matches": [
{
"kra_text": "Monitors CI/CD pipeline reliability, identifies bottlenecks in delivery workflows, and improves deployment frequency, lead time, and failure recovery rate.",
"sentence": "build observability into our solutions to monitor production health, help to resolve incidents, and remediate the root cause of risks and issues.",
"similarity": 0.5558
},
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "a proven track of work experience in cloud deployments (MS Azure preferred) in an agile SDLC environment, leveraging modern programming languages, DevOps, SQL and noSQL databases, and test-driven development.",
"similarity": 0.4933
},
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "continuously up-skill, learn new technologies and practices, reuse strategic platforms and standards, evaluate options, and make decisions with long-term sustainability in mind.",
"similarity": 0.4176
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 10,
"score": 0.4889,
"slug": "devops-engineer",
"total_count": null
},
{
"display_name": "Backend Developer",
"kra_matches": [
{
"kra_text": "Adds structured logging, metrics, distributed tracing, and alerting to improve system observability and support production debugging.",
"sentence": "build observability into our solutions to monitor production health, help to resolve incidents, and remediate the root cause of risks and issues.",
"similarity": 0.6114
},
{
"kra_text": "Configures Docker containers, deployment descriptors, environment variables, and CI/CD pipeline stages for backend service releases.",
"sentence": "a proven track of work experience in cloud deployments (MS Azure preferred) in an agile SDLC environment, leveraging modern programming languages, DevOps, SQL and noSQL databases, and test-driven development.",
"similarity": 0.4082
},
{
"kra_text": "Writes database access logic including SQL queries, ORM mappings, stored procedures, and migration scripts for relational databases like PostgreSQL and MySQL.",
"sentence": "a strong knowledge of one or more of Oracle and PL/SQL, Postgres, Informatica ETL, Tableau, Business Objects, PowerBI, Azure Synapse Analytics.",
"similarity": 0.4018
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 1,
"score": 0.4738,
"slug": "backend-engineer",
"total_count": null
},
{
"display_name": "Cyber Security Engineer",
"kra_matches": [
{
"kra_text": "Defines secure engineering standards, secure coding guidelines, threat intelligence feeds, and compliance requirements for the organization.",
"sentence": "ensure the quality, security, reliability, and compliance of our solutions by applying our digital principles and implementing both functional and non-functional requirements.",
"similarity": 0.5945
},
{
"kra_text": "Defines secure engineering standards, secure coding guidelines, threat intelligence feeds, and compliance requirements for the organization.",
"sentence": "continuously up-skill, learn new technologies and practices, reuse strategic platforms and standards, evaluate options, and make decisions with long-term sustainability in mind.",
"similarity": 0.4226
},
{
"kra_text": "Performs threat modeling, security architecture reviews, and quantitative risk analysis for new product features and infrastructure changes.",
"sentence": "Design and develop new cloud-based data analytics products and services for UBS HR",
"similarity": 0.4029
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 5,
"score": 0.4733,
"slug": "cybersecurity-engineer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": 5,
"matched_skills": [
"Azure",
"Azure Synapse Analytics",
"Power BI",
"SQL",
"Tableau"
],
"role_id": 2,
"score": 0.25,
"slug": "data-engineer",
"total_count": 20
},
{
"display_name": "Backend Developer",
"kra_matches": null,
"matched_count": 3,
"matched_skills": [
"Azure",
"NoSQL",
"PostgreSQL"
],
"role_id": 1,
"score": 0.15,
"slug": "backend-engineer",
"total_count": 20
},
{
"display_name": "Fullstack Developer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"Azure",
"PostgreSQL"
],
"role_id": 15,
"score": 0.1,
"slug": "full-stack-engineer",
"total_count": 20
},
{
"display_name": "DevOps Engineer",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"Azure",
"DevOps"
],
"role_id": 10,
"score": 0.1,
"slug": "devops-engineer",
"total_count": 20
},
{
"display_name": "Cloud Architect",
"kra_matches": null,
"matched_count": 2,
"matched_skills": [
"Azure",
"DevOps"
],
"role_id": 9,
"score": 0.1,
"slug": "cloud-architect",
"total_count": 20
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "A",
"chosen_role": {
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 1.0,
"slug": "data-engineer",
"total_count": null
},
"confidence": 1.0,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [],
"matched_kras": [],
"matched_skills": [],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.25 does not contradict",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 148,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 7990,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Azure Data Factory",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 7991,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Azure Databricks",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 7992,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Oracle",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 7993,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Informatica ETL",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 7994,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Business Objects",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 7995,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Test-Driven Development",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 7996,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "SAP Business Objects",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 7997,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Tableau Desktop",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 7998,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Tableau Server",
"status": "pending"
}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{
"alias_matches": [
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 407,
"existing_alias_text": "Azure",
"input_term": "Azure",
"matched_canonical": {
"category_id": 9,
"display_name": "Azure",
"id": 188,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
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}
],
"input_skill": "Tableau Desktop",
"matched_via": "embedding_alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Tableau",
"alias_type": "CANONICAL",
"id": 359,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 9,
"display_name": "Tableau",
"id": 150,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "tableau",
"sub_category_id": 111,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "BI and Visualization Tools",
"id": 31,
"rationale": "Tools used to expose curated data to analysts and business users through dashboards, reports, and semantic exploration. Data engineers support these tools by shaping reliable datasets and performant models.",
"slug": "bi-and-visualization-tools",
"source": "db"
},
"input_skill": "Tableau Server",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_skill": "Tableau Server",
"matched_via": "embedding_alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"Azure Data Factory",
"Azure Databricks",
"Oracle",
"Informatica ETL",
"Business Objects",
"Test-Driven Development",
"SAP Business Objects"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Data Engineer",
"id": 2,
"rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.25 does not contradict",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Azure",
"tag": "in_db"
},
{
"skill": "Azure Data Factory",
"tag": "new"
},
{
"skill": "Azure Databricks",
"tag": "new"
},
{
"skill": "Oracle",
"tag": "new"
},
{
"skill": "PL/SQL",
"tag": "in_db"
},
{
"skill": "PostgreSQL",
"tag": "in_db"
},
{
"skill": "Informatica ETL",
"tag": "new"
},
{
"skill": "Tableau",
"tag": "in_db"
},
{
"skill": "Business Objects",
"tag": "new"
},
{
"skill": "Power BI",
"tag": "in_db"
},
{
"skill": "Azure Synapse Analytics",
"tag": "in_db"
},
{
"skill": "SQL",
"tag": "in_db"
},
{
"skill": "NoSQL",
"tag": "in_db"
},
{
"skill": "Agile",
"tag": "in_db"
},
{
"skill": "SDLC",
"tag": "in_db"
},
{
"skill": "DevOps",
"tag": "in_db"
},
{
"skill": "Test-Driven Development",
"tag": "new"
},
{
"skill": "SAP Business Objects",
"tag": "new"
},
{
"skill": "Tableau Desktop",
"tag": "in_db"
},
{
"skill": "Tableau Server",
"tag": "in_db"
}
],
"llm_cost_api1_usd": null,
"llm_cost_api2_usd": null,
"llm_cost_api3_usd": null,
"llm_cost_total_usd": null,
"persistence": {
"items": [
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms",
"id": 20,
"rationale": "Underlying cloud providers that host the managed services or infrastructure used by the role, such as AWS, Azure, and GCP.",
"slug": "cloud-platforms",
"source": "db"
},
"dimension_id": 20,
"input_skill": "Azure",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Java Backend Developer",
"id": 79,
"rationale": null,
"role_archetype": "Engineering",
"slug": "java-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms \u0026 Managed Services",
"id": 221,
"rationale": "Operates and integrates vendor-specific cloud compute, storage, and hosting services.",
"slug": "cloud-platforms-managed-services",
"source": "db"
},
"dimension_id": 221,
"input_skill": "Azure",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Platforms for AI Deployment",
"id": 211,
"rationale": "Major cloud services that provide infrastructure and managed services for AI workloads.",
"slug": "cloud-platforms-for-ai-deployment",
"source": "db"
},
"dimension_id": 211,
"input_skill": "Azure",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "AI Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Provider Platforms",
"id": 131,
"rationale": "Major cloud platforms and their core service ecosystems used to design target-state architectures, choose deployment boundaries, and evaluate managed capabilities. This is the primary substrate for cloud architecture decisions.",
"slug": "cloud-provider-platforms",
"source": "db"
},
"dimension_id": 131,
"input_skill": "Azure",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
},
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Posture Tools",
"id": 64,
"rationale": "Cloud-native security platforms used to assess misconfiguration, workload exposure, and cloud control coverage. This dimension includes the major CNAPP/CSPM/CWPP vendors and cloud security services the role reviews and tunes.",
"slug": "cloud-security-posture-tools",
"source": "db"
},
"dimension_id": 64,
"input_skill": "Azure",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 188,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 96,
"input_skill": "PL/SQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 1567,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Data Modeling",
"id": 216,
"rationale": "Modeling and tuning relational persistence for backend features. PHP backend developers need this to shape schemas, indexes, transactions, and query-aware data structures that support application behavior.",
"slug": "relational-data-modeling",
"source": "db"
},
"dimension_id": 216,
"input_skill": "PostgreSQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Fullstack Developer",
"id": 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"
},
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 16,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Database Design",
"id": 4,
"rationale": "Modeling and operating relational persistence for backend services. Includes schema design, normalization, indexing, transactions, and query tuning for operational data stores.",
"slug": "relational-database-design",
"source": "db"
},
"dimension_id": 4,
"input_skill": "PostgreSQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "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": "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": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Ruby Backend Developer",
"id": 85,
"rationale": null,
"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 16,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Database Usage",
"id": 371,
"rationale": "Working effectively with operational relational databases from Go backend services. This includes schema-aware querying, indexing awareness, transactions, and understanding how service code interacts with PostgreSQL or similar systems.",
"slug": "relational-database-usage",
"source": "db"
},
"dimension_id": 371,
"input_skill": "PostgreSQL",
"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": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 16,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "BI and Visualization Tools",
"id": 31,
"rationale": "Tools used to expose curated data to analysts and business users through dashboards, reports, and semantic exploration. Data engineers support these tools by shaping reliable datasets and performant models.",
"slug": "bi-and-visualization-tools",
"source": "db"
},
"dimension_id": 31,
"input_skill": "Tableau",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 150,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "BI and Visualization Tools",
"id": 31,
"rationale": "Tools used to expose curated data to analysts and business users through dashboards, reports, and semantic exploration. Data engineers support these tools by shaping reliable datasets and performant models.",
"slug": "bi-and-visualization-tools",
"source": "db"
},
"dimension_id": 31,
"input_skill": "Power BI",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 151,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"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": "Azure Synapse Analytics",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 108,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Pega Programming Languages \u0026 DSLs",
"id": 267,
"rationale": "Programming languages and domain-specific languages used in Pega development.",
"slug": "pega-programming-languages-dsls",
"source": "db"
},
"dimension_id": 267,
"input_skill": "SQL",
"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": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 101,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 21,
"input_skill": "SQL",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 101,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"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"
},
"dimension_id": 19,
"input_skill": "NoSQL",
"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"
}
],
"skill_dimension_saved": true,
"skill_id": 1346,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
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"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
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{
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{
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{
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},
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{
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{
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{
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],
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],
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}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.