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Pipeline run

785fe599-c02a-4bea-b58b-4fd37285990e

Pipeline LLM cost (USD)
API 1: $0.0094 API 2: $0.0005 API 3: $0.0000 Total: $0.0099

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
role baseline loaded sources · ai_index: jd · nature_of_work: jd · tech_stack_maturity: jd
Nature of work · Data pipeline development
Build ETL/ELT pipelines and data integration frameworks, design DWH/OLTP/OLAP databases, and tune SQL, indexes, and stored procedures across RDBMS/NoSQL and cloud setups; also handle multiple source formats and reporting data prep.
"Build DWH and data sync pipeline from Transactional Database and external data sources."
Tech stack maturity
Mainstream Modern
The skill mix of Python, SQL, RDBMS, and NoSQL is broadly common in current data engineering roles and aligns with standard modern data platforms rather than bleeding-edge or legacy-only stacks.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
0.00 / 5
· Title match
· Has AI skill
· AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3):
Evidence — skills matched in JD (27)
ETL ELT Data Integration Data Warehouse SQL Python OLTP OLAP RDBMS NoSQL JSON XML CSV Excel Power BI Amazon QuickSight SSRS Stored Procedures Functions Tables Views Triggers Indexes Query Optimization Performance Tuning +2
Skill cluster (7 dimension groups, role-scoped)
Programming Languages for Data Work
SQL Python
API Interface and Contract Design
JSON
BI and Visualization Tools
Power BI
Cloud Platforms
Cloud
Performance and Cost Optimization
Query Optimization
Relational Database Design
Indexes
Cross-cutting / unaligned
ETL ELT Data Integration Data Warehouse OLTP OLAP RDBMS NoSQL XML CSV Excel Amazon QuickSight SSRS Stored Procedures Functions Tables Views Triggers Performance Tuning Job Scheduling
Show KRA description ↓
• Develop data integration framework from various sources. • Build DWH and data sync pipeline from Transactional Database and external data sources. • Application Database design and development. • Performance Tuning and Query Optimization • Writing and optimizing complex queries. • Experience of working on ETL/ELT. Able to write data flow pipeline from scratch. • In-depth knowledge of OLTP, OLAP & DWH concepts and best design practices. • Experience of DWH design and development. • Worked on various data formats like JSON, XML, CSV, EXCEL, and TXT. • Experience of any reporting tool like Power BI, Quick Sight or SSRS. o Must have handled VLDB. • Working as a contributor in current role. • In-depth knowledge of database architecture, experience of working with any RDBMS. • Experience in Performance Tuning and Query Optimization. • Hands on experience of writing stored procs, functions, tables, views, triggers. • Strong knowledge of indexes and index management. • Hands on database development, ability to write and troubleshoot SQL Code • Should have good exposure on data integration from multiple sources. • Playing a key role in designing, developing, and implementing the database for various products • Experience of any NOSQL database. • Working in Cloud Environment. • Experience of working with Python. o Knowledge of jobs, job scheduling alternatives. • Finance Domain knowledge. • Strong written/oral communication, presentation, and interpersonal skill

Signals

Skill backend-engineer
0.20
Alias data-engineer
1.00
KRA svelte-frontend-developer
0.67

Post-classification

Centroidupdated · n=77
Alias collision log
New-role queue
New skills captured16
New KRA captured

Captured for admin review

ETL primary Data Engineer pending
ELT primary Data Engineer pending
Data Integration primary Data Engineer pending
Data Warehouse primary Data Engineer pending
OLTP primary Data Engineer pending
OLAP primary Data Engineer pending
CSV Data Engineer pending
Excel Data Engineer pending
Amazon QuickSight Data Engineer pending
SSRS Data Engineer pending
Stored Procedures Data Engineer pending
Functions Data Engineer pending
Tables Data Engineer pending
Triggers Data Engineer pending
Performance Tuning Data Engineer pending
Job Scheduling Data Engineer pending
Status: completed Created: 2026-05-27T13:47:21.855781Z Updated: 2026-05-27T13:50:23.225907Z API 3 duration: 45546 ms
Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

Data Engineer

domain · Data Engineering & Analytics CASE DOMAIN

slug: data-engineer · id: 2 · source: db

Domain=Data Engineering & Analytics; The JD centers on end-to-end data integration, ETL/ELT pipelines, DWH development, SQL/database tuning, and cloud/Python work, which best fits a Data Engineer.

Matched skills

ETL/ELTDWHOLTPOLAPJSONXMLCSVEXCELTXTPower BIQuick SightSSRSRDBMSstored procsfunctionstablesviewstriggersindexesSQL

Matched dimensions

Data Integration EngineeringData Warehouse DevelopmentDatabase Performance TuningSQL Development and OptimizationCloud Data EngineeringReporting Tool SupportDatabase ArchitectureData Pipeline Development

Matched KRAs

Develop data integration framework from various sourcesBuild DWH and data sync pipelineWriting and optimizing complex queriesWrite data flow pipeline from scratchExperience of DWH design and developmentHands on database developmentPlaying a key role in designing, developing, and implementing the databaseWorking in Cloud Environment

Resolution: in_db — role exists in library; skill↔dim and role↔dim links saved when applicable.

0
New skills
0
Skill↔dim saved
0
Role↔dim saved
1
Skipped

Job description

Job Summary: This position is for an experienced ETL & Datawarehouse Developer with a focus on integration of data from various sources. Database Lead will be part of scrum team to help the engineering team in agile fashion.

 Responsibilities

• Develop data integration framework from various sources.
• Build DWH and data sync pipeline from Transactional Database and external data sources.
• Application Database design and development.
• Performance Tuning and Query Optimization
• Writing and optimizing complex queries.


Skills and Experience: **

• Primary
• Experience of working on ETL/ELT. Able to write data flow pipeline from scratch.
• In-depth knowledge of OLTP, OLAP & DWH concepts and best design practices.
• Experience of DWH design and development.
• Worked on various data formats like JSON, XML, CSV, EXCEL, and TXT.
• Experience of any reporting tool like Power BI, Quick Sight or SSRS. o Must have handled VLDB.
• Working as a contributor in current role.


** Secondary **

• In-depth knowledge of database architecture, experience of working with any RDBMS.
• Experience in Performance Tuning and Query Optimization.
• Hands on experience of writing stored procs, functions, tables, views, triggers.
• Strong knowledge of indexes and index management.
• Hands on database development, ability to write and troubleshoot SQL Code
• Should have good exposure on data integration from multiple sources.
• Playing a key role in designing, developing, and implementing the database for various products
• Experience of any NOSQL database.


** Desirable**

• Working in Cloud Environment.
• Experience of working with Python. o Knowledge of jobs, job scheduling alternatives.
• Finance Domain knowledge.
• Strong written/oral communication, presentation, and interpersonal skill


Education: bachelor’s degree in computer Sc., Information System, or related disciplines

Skills from this JD

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

ETL Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
ELT Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Integration Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Warehouse Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Databases
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
SQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: SQL id=101 · sql

Aliases — catalog

  • SQL (CANONICAL) primary

Context tags (catalog)

ACID CTE DDL DML ETL JOIN MySQL NoSQL OLAP ORM PostgreSQL SQL injection SQLite T-SQL data modeling data warehousing database normalization execution plan indexing joins normalization query optimization stored procedures subquery transaction isolation transaction management window functions

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

Aliases — catalog

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

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

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

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Fullstack Developer

  • Programming Languages and Scripting Catalog dimension db id 59

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • Programming Languages for XR Catalog dimension db id 97

    Library dimension (catalog)

    Roles linked in library: AR/VR Engineer

  • Python Programming Catalog dimension db id 290

    Library dimension (catalog)

    Roles linked in library: Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
OLTP Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Databases
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
OLAP Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Databases
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
RDBMS Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: RDBMS id=1355 · rdbms

Aliases — catalog

  • RDBMS (CANONICAL)

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
NoSQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: NoSQL id=1346 · nosql

Aliases — catalog

  • NoSQL (CANONICAL)

Context tags (catalog)

CAP theorem Cassandra DynamoDB MongoDB Redis column-family data modeling document store eventual consistency graph database horizontal scaling key-value store query language schema-less sharding

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)
JSON Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: JSON id=1984 · json

Aliases — catalog

  • JSON (CANONICAL) primary

Context tags (catalog)

AJAX API JSON Schema JSON-LD JSONP JavaScript NoSQL REST configuration data binding data format data interchange data structure deserialization interoperability key-value pairs lightweight object notation schema serialization text-based

Stored enrichment (catalog DB)

Category
Format
Sub-category
Data Interchange Format
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: JSON is a default data interchange format in APIs and web stacks; it appears in a very high volume of job descriptions and is supported by every major language/runtime.

Skill profile (library / DB)

Skill nature
STANDARD
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
4
Sub-category id
1457
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • API Integration and Data Fetching Catalog dimension db id 127

    Library dimension (catalog)

    Roles linked in library: Angular Frontend Developer, Frontend Developer, Fullstack Developer, React Frontend Developer, Svelte Frontend Developer, Vue Frontend Developer, Web Developer

  • API Interface and Contract Design Catalog dimension db id 289

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Go Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer

  • Integration Protocols & Standards Catalog dimension db id 271

    Library dimension (catalog)

    Roles linked in library: Pega Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
API Integration and Data Fetching
api-integration-and-data-fetching
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
API Interface and Contract Design
api-interface-and-contract-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Integration Protocols & Standards
integration-protocols-standards
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
XML Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: XML id=1636 · xml

Aliases — catalog

  • XML (CANONICAL) primary

Context tags (catalog)

Atom DOM DTD Data Interchange Data Serialization JSON Markup Language Namespaces Parsing RSS SAX SOAP SVG Serialization Well-formed XML Schema XPath XQuery XSLT

Stored enrichment (catalog DB)

Category
Format
Sub-category
Markup Format
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: XML remains a common requirement in JDs for enterprise integration, SOAP, RSS, and config files; it’s still widely supported across major platforms rather than being sunset or replaced outright.

Skill profile (library / DB)

Skill nature
STANDARD
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
4
Sub-category id
689
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Integration Protocols & Standards Catalog dimension db id 271

    Library dimension (catalog)

    Roles linked in library: Pega Developer

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Integration Protocols & Standards
integration-protocols-standards
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CSV Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Excel Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Power BI Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Power BI id=151 · power-bi

Aliases — catalog

  • Power BI (CANONICAL) primary

Context tags (catalog)

Azure Synapse DAX DirectQuery Import mode M language Power Query RLS SQL Server SSAS dashboard data modeling data warehouse gateway reporting star schema

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
Amazon QuickSight Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Business Intelligence Tools
Sub-category
general
Skill nature
PLATFORM
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
SSRS Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Business Intelligence Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Stored Procedures Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Databases
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Functions Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Databases
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Tables Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Databases
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Views Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Views id=3116 · views

Aliases — catalog

  • Views (CANONICAL) primary

Context tags (catalog)

AJAX CRUD operations MVC RESTful API UI components client-side rendering component lifecycle data binding data visualization dynamic content event handling query builder server-side rendering state management template rendering

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Query Builder Framework
Vendor
null
License
unknown
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: “Views” as a query-builder framework has low JD volume and is largely overshadowed by ORM/query tools like Django ORM, SQLAlchemy, and Knex in current postings and docs.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
2424
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Views and Content Querying Catalog dimension db id 347

    Library dimension (catalog)

    Roles linked in library: Drupal Dev

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Views and Content Querying
views-and-content-querying
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Triggers Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Databases
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Indexes Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Indexes id=1428 · indexes

Aliases — catalog

  • Indexes (CANONICAL) primary
  • indexes (CANONICAL)

Context tags (catalog)

B-tree MySQL NoSQL PostgreSQL SQL SQL Server SQL indexing bitmap index clustered index composite index data retrieval database optimization database performance full-text index full-text search hash index index fragmentation index maintenance index scan index seek indexing strategy non-clustered index query optimization query performance scan vs seek unique index

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Database Indexing
Confidence
0.88
Version strategy
NOT_APPLICABLE

Maturity reasoning: Database indexes are a standard topic in SQL/NoSQL job descriptions and core interview screens; they’re broadly used across PostgreSQL, MySQL, and MongoDB for query performance tuning.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
2477
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, 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)
Query Optimization Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: query optimization id=160 · query-optimization

Aliases — catalog

  • query optimization (CANONICAL) primary
  • Query optimization (CANONICAL)

Context tags (catalog)

B-tree EXPLAIN SQL performance caching cardinality estimation cost-based optimizer covering index data retrieval database partitioning database schema database tuning denormalization execution plan index scan indexing join algorithms join order join strategies load balancing materialized view materialized views normalization partition pruning partitioning query plan query profiling query rewriting slow query log statistics subqueries table scan

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Performance Optimization Concept
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common in DB/perf job descriptions and interview loops; vendors like PostgreSQL, MySQL, and SQL Server all document EXPLAIN/ANALYZE and indexing as standard tuning practices.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
679
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Performance and Cost Optimization Catalog dimension db id 33

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Performance and Scalability Tuning Catalog dimension db id 11

    Library dimension (catalog)

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

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Performance and Cost Optimization
performance-and-cost-optimization
Existing dimension (library) · Role↔dimension saved
Performance and Scalability Tuning
performance-and-scalability-tuning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Performance Tuning Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: query tuning id=3553 · query-tuning

Aliases — catalog

  • query tuning (CANONICAL) primary
  • Query Tuning (CANONICAL)

Context tags (catalog)

SQL SQL optimization caching cost estimation cost-based optimization data retrieval database indexing database optimization database performance database profiling database statistics database tuning execution plan execution time indexing join strategies load balancing parameter sniffing query analysis query complexity query execution query performance query profiling query rewriting resource allocation resource utilization statistics

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Query Optimization
Confidence
0.82
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common in DB/analytics job descriptions and vendor docs; PostgreSQL, MySQL, SQL Server, and Oracle all expose EXPLAIN/ANALYZE and tuning guides, showing broad hiring-pipeline demand.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
3067
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • 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

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Relational Database Design
relational-database-design
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Job Scheduling Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Cloud Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Cloud id=1572 · cloud

Aliases — catalog

  • Cloud (CANONICAL)

Context tags (catalog)

AWS Azure DevOps Docker Google Cloud IaaS Kubernetes PaaS SaaS cloud migration cloud security hybrid cloud microservices multi-cloud serverless

Stored enrichment (catalog DB)

Category
Domain
Sub-category
Cloud Computing
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: Cloud is a hiring-pipeline staple: AWS, Azure, and GCP appear in a large share of modern infrastructure JDs, and major vendors continue expanding cloud services rather than sunsetting them.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
37
Sub-category id
1177
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

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved

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
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
Python in_db
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension saved
Python in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
RDBMS in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
NoSQL in_db
NoSQL Databases
nosql-databases
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JSON in_db
API Integration and Data Fetching
api-integration-and-data-fetching
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JSON in_db
API Interface and Contract Design
api-interface-and-contract-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JSON in_db
Integration Protocols & Standards
integration-protocols-standards
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
XML in_db
Integration Protocols & Standards
integration-protocols-standards
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
XML in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Power BI in_db
BI and Visualization Tools
bi-and-visualization-tools
Existing dimension (library) · Role↔dimension saved
Views in_db
Views and Content Querying
views-and-content-querying
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Indexes in_db
Relational Data Modeling
relational-data-modeling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Indexes in_db
Relational Database Design
relational-database-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Indexes in_db
Relational Database Usage
relational-database-usage
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Query Optimization in_db
Performance and Cost Optimization
performance-and-cost-optimization
Existing dimension (library) · Role↔dimension saved
Query Optimization in_db
Performance and Scalability Tuning
performance-and-scalability-tuning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Performance Tuning new
Relational Database Design
relational-database-design
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Cloud in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved

Library artifacts (this run)

Kind Detail DB id
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 Data Integration | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Data Warehouse | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed OLTP | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed OLAP | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed CSV | type=Data Engineering Tools subtype=general nature=LANGUAGE lifespan=EVERGREEN
canonical_skill_proposed Excel | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Amazon QuickSight | type=Business Intelligence Tools subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed SSRS | type=Business Intelligence Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Stored Procedures | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Functions | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Tables | type=Databases subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed Triggers | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Job Scheduling | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
dimension_skill_link_proposed Performance Tuning ↔ Relational Database Design
nano JD Parser — gpt-4.1-nano click to toggle
RoleETL & Datawarehouse Developer
DomainOther
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": null,
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "Other"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "BTECH/BE - Computer Science / Information Systems (or related)",
      "raw": "bachelor\u2019s degree in computer Sc., Information System, or related disciplines",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": null,
    "min": null,
    "raw": null
  },
  "job_locations": [],
  "role": "ETL \u0026 Datawarehouse Developer",
  "role_aliases": [
    "Data Engineer",
    "ETL Developer",
    "Data Warehouse Developer"
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  "role_archetype": "Data",
  "roles_and_responsibilities": [
    {
      "bullet_count": 5,
      "heading": "Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Develop data integration framework",
        "last_5_words": "and optimizing complex queries."
      },
      "text": "\u2022 Develop data integration framework from various sources.\n\u2022 Build DWH and data sync pipeline from Transactional Database and external data sources.\n\u2022 Application Database design and development.\n\u2022 Performance Tuning and Query Optimization\n\u2022 Writing and optimizing complex queries.",
      "word_count": 41
    },
    {
      "bullet_count": 6,
      "heading": "Skills and Experience: Primary",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Experience of working on ETL/ELT.",
        "last_5_words": "in current role."
      },
      "text": "\u2022 Experience of working on ETL/ELT. Able to write data flow pipeline from scratch.\n\u2022 In-depth knowledge of OLTP, OLAP \u0026 DWH concepts and best design practices.\n\u2022 Experience of DWH design and development.\n\u2022 Worked on various data formats like JSON, XML, CSV, EXCEL, and TXT.\n\u2022 Experience of any reporting tool like Power BI, Quick Sight or SSRS. o Must have handled VLDB.\n\u2022 Working as a contributor in current role.",
      "word_count": 66
    },
    {
      "bullet_count": 8,
      "heading": "Skills and Experience: Secondary",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 In-depth knowledge of database architecture,",
        "last_5_words": "any NOSQL database."
      },
      "text": "\u2022 In-depth knowledge of database architecture, experience of working with any RDBMS.\n\u2022 Experience in Performance Tuning and Query Optimization.\n\u2022 Hands on experience of writing stored procs, functions, tables, views, triggers.\n\u2022 Strong knowledge of indexes and index management.\n\u2022 Hands on database development, ability to write and troubleshoot SQL Code\n\u2022 Should have good exposure on data integration from multiple sources.\n\u2022 Playing a key role in designing, developing, and implementing the database for various products\n\u2022 Experience of any NOSQL database.",
      "word_count": 83
    },
    {
      "bullet_count": 4,
      "heading": "Skills and Experience: Desirable",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Working in Cloud Environment.",
        "last_5_words": "presentation, and interpersonal skill"
      },
      "text": "\u2022 Working in Cloud Environment.\n\u2022 Experience of working with Python. o Knowledge of jobs, job scheduling alternatives.\n\u2022 Finance Domain knowledge.\n\u2022 Strong written/oral communication, presentation, and interpersonal skill",
      "word_count": 41
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "ETL"
    },
    {
      "is_primary": true,
      "skill_name": "ELT"
    },
    {
      "is_primary": true,
      "skill_name": "Data Integration"
    },
    {
      "is_primary": true,
      "skill_name": "Data Warehouse"
    },
    {
      "is_primary": true,
      "skill_name": "SQL"
    },
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "OLTP"
    },
    {
      "is_primary": true,
      "skill_name": "OLAP"
    },
    {
      "is_primary": true,
      "skill_name": "RDBMS"
    },
    {
      "is_primary": true,
      "skill_name": "NoSQL"
    },
    {
      "is_primary": false,
      "skill_name": "JSON"
    },
    {
      "is_primary": false,
      "skill_name": "XML"
    },
    {
      "is_primary": false,
      "skill_name": "CSV"
    },
    {
      "is_primary": false,
      "skill_name": "Excel"
    },
    {
      "is_primary": false,
      "skill_name": "Power BI"
    },
    {
      "is_primary": false,
      "skill_name": "Amazon QuickSight"
    },
    {
      "is_primary": false,
      "skill_name": "SSRS"
    },
    {
      "is_primary": false,
      "skill_name": "Stored Procedures"
    },
    {
      "is_primary": false,
      "skill_name": "Functions"
    },
    {
      "is_primary": false,
      "skill_name": "Tables"
    },
    {
      "is_primary": false,
      "skill_name": "Views"
    },
    {
      "is_primary": false,
      "skill_name": "Triggers"
    },
    {
      "is_primary": false,
      "skill_name": "Indexes"
    },
    {
      "is_primary": false,
      "skill_name": "Query Optimization"
    },
    {
      "is_primary": false,
      "skill_name": "Performance Tuning"
    },
    {
      "is_primary": false,
      "skill_name": "Job Scheduling"
    },
    {
      "is_primary": false,
      "skill_name": "Cloud"
    }
  ],
  "jd_role": {
    "display_name": "ETL \u0026 Datawarehouse Developer",
    "rationale": null,
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      "Data Engineer",
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    "role_archetype": "Data",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": null,
    "certifications": [],
    "company_name": null,
    "ctc": null,
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      },
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    },
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      {
        "level": "Bachelor\u0027s",
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    ],
    "experience": {
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    },
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    "role_archetype": "Data",
    "roles_and_responsibilities": [
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        "bullet_count": 5,
        "heading": "Responsibilities",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Develop data integration framework",
          "last_5_words": "and optimizing complex queries."
        },
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      },
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        "bullet_count": 6,
        "heading": "Skills and Experience: Primary",
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        "source_marker": {
          "first_5_words": "\u2022 Experience of working on ETL/ELT.",
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        },
        "text": "\u2022 Experience of working on ETL/ELT. Able to write data flow pipeline from scratch.\n\u2022 In-depth knowledge of OLTP, OLAP \u0026 DWH concepts and best design practices.\n\u2022 Experience of DWH design and development.\n\u2022 Worked on various data formats like JSON, XML, CSV, EXCEL, and TXT.\n\u2022 Experience of any reporting tool like Power BI, Quick Sight or SSRS. o Must have handled VLDB.\n\u2022 Working as a contributor in current role.",
        "word_count": 66
      },
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        "bullet_count": 8,
        "heading": "Skills and Experience: Secondary",
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        "source_marker": {
          "first_5_words": "\u2022 In-depth knowledge of database architecture,",
          "last_5_words": "any NOSQL database."
        },
        "text": "\u2022 In-depth knowledge of database architecture, experience of working with any RDBMS.\n\u2022 Experience in Performance Tuning and Query Optimization.\n\u2022 Hands on experience of writing stored procs, functions, tables, views, triggers.\n\u2022 Strong knowledge of indexes and index management.\n\u2022 Hands on database development, ability to write and troubleshoot SQL Code\n\u2022 Should have good exposure on data integration from multiple sources.\n\u2022 Playing a key role in designing, developing, and implementing the database for various products\n\u2022 Experience of any NOSQL database.",
        "word_count": 83
      },
      {
        "bullet_count": 4,
        "heading": "Skills and Experience: Desirable",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Working in Cloud Environment.",
          "last_5_words": "presentation, and interpersonal skill"
        },
        "text": "\u2022 Working in Cloud Environment.\n\u2022 Experience of working with Python. o Knowledge of jobs, job scheduling alternatives.\n\u2022 Finance Domain knowledge.\n\u2022 Strong written/oral communication, presentation, and interpersonal skill",
        "word_count": 41
      }
    ],
    "urls": []
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "785fe599-c02a-4bea-b58b-4fd37285990e",
  "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": "Svelte Frontend Developer",
        "kra_matches": [
          {
            "kra_text": "performance tuning",
            "sentence": "Performance Tuning and Query Optimization",
            "similarity": 0.7816
          },
          {
            "kra_text": "backend data integration",
            "sentence": "Develop data integration framework from various sources.",
            "similarity": 0.6382
          },
          {
            "kra_text": "backend data integration",
            "sentence": "Build DWH and data sync pipeline from Transactional Database and external data sources.",
            "similarity": 0.5762
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 92,
        "score": 0.6653,
        "slug": "svelte-frontend-developer",
        "total_count": null
      },
      {
        "display_name": "Data Engineer",
        "kra_matches": [
          {
            "kra_text": "Builds data ingestion pipelines to collect data from transactional databases, third-party APIs, event streams, and file sources into centralized data platforms.",
            "sentence": "Build DWH and data sync pipeline from Transactional Database and external data sources.",
            "similarity": 0.6402
          },
          {
            "kra_text": "Builds data ingestion pipelines to collect data from transactional databases, third-party APIs, event streams, and file sources into centralized data platforms.",
            "sentence": "Develop data integration framework from various sources.",
            "similarity": 0.5813
          },
          {
            "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": "In-depth knowledge of OLTP, OLAP \u0026 DWH concepts and best design practices.",
            "similarity": 0.5677
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 0.5964,
        "slug": "data-engineer",
        "total_count": null
      },
      {
        "display_name": "Scala Backend Developer",
        "kra_matches": [
          {
            "kra_text": "performance and reliability tuning",
            "sentence": "Performance Tuning and Query Optimization",
            "similarity": 0.6709
          },
          {
            "kra_text": "application data modeling",
            "sentence": "Application Database design and development.",
            "similarity": 0.6378
          },
          {
            "kra_text": "internal and external system integration",
            "sentence": "Develop data integration framework from various sources.",
            "similarity": 0.4416
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 87,
        "score": 0.5834,
        "slug": "scala-backend-developer",
        "total_count": null
      },
      {
        "display_name": "Flutter Developer",
        "kra_matches": [
          {
            "kra_text": "integrate external APIs and data sources",
            "sentence": "Develop data integration framework from various sources.",
            "similarity": 0.6362
          },
          {
            "kra_text": "optimize responsiveness and performance",
            "sentence": "Performance Tuning and Query Optimization",
            "similarity": 0.5163
          },
          {
            "kra_text": "integrate external APIs and data sources",
            "sentence": "Should have good exposure on data integration from multiple sources.",
            "similarity": 0.5118
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 74,
        "score": 0.5547,
        "slug": "flutter-developer",
        "total_count": null
      },
      {
        "display_name": "Java Backend Developer",
        "kra_matches": [
          {
            "kra_text": "backend performance tuning",
            "sentence": "Performance Tuning and Query Optimization",
            "similarity": 0.7173
          },
          {
            "kra_text": "persistence and data modeling",
            "sentence": "In-depth knowledge of OLTP, OLAP \u0026 DWH concepts and best design practices.",
            "similarity": 0.4606
          },
          {
            "kra_text": "external system integration",
            "sentence": "Develop data integration framework from various sources.",
            "similarity": 0.4566
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 79,
        "score": 0.5448,
        "slug": "java-backend-developer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "NoSQL",
          "Python"
        ],
        "role_id": 1,
        "score": 0.2,
        "slug": "backend-engineer",
        "total_count": 10
      },
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "Python",
          "SQL"
        ],
        "role_id": 2,
        "score": 0.2,
        "slug": "data-engineer",
        "total_count": 10
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Python"
        ],
        "role_id": 3,
        "score": 0.1,
        "slug": "ml-engineer",
        "total_count": 10
      },
      {
        "display_name": "Cyber Security Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Python"
        ],
        "role_id": 5,
        "score": 0.1,
        "slug": "cybersecurity-engineer",
        "total_count": 10
      },
      {
        "display_name": "AR/VR Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Python"
        ],
        "role_id": 8,
        "score": 0.1,
        "slug": "ar-vr-engineer",
        "total_count": 10
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "DOMAIN",
    "chosen_role": {
      "display_name": "Data Engineer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 2,
      "score": 0.94,
      "slug": "data-engineer",
      "total_count": null
    },
    "confidence": 0.94,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [
      "Data Integration Engineering",
      "Data Warehouse Development",
      "Database Performance Tuning",
      "SQL Development and Optimization",
      "Cloud Data Engineering",
      "Reporting Tool Support",
      "Database Architecture",
      "Data Pipeline Development"
    ],
    "matched_kras": [
      "Develop data integration framework from various sources",
      "Build DWH and data sync pipeline",
      "Writing and optimizing complex queries",
      "Write data flow pipeline from scratch",
      "Experience of DWH design and development",
      "Hands on database development",
      "Playing a key role in designing, developing, and implementing the database",
      "Working in Cloud Environment"
    ],
    "matched_skills": [
      "ETL/ELT",
      "DWH",
      "OLTP",
      "OLAP",
      "JSON",
      "XML",
      "CSV",
      "EXCEL",
      "TXT",
      "Power BI",
      "Quick Sight",
      "SSRS",
      "RDBMS",
      "stored procs",
      "functions",
      "tables",
      "views",
      "triggers",
      "indexes",
      "SQL"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=Data Engineering \u0026 Analytics; The JD centers on end-to-end data integration, ETL/ELT pipelines, DWH development, SQL/database tuning, and cloud/Python work, which best fits a Data Engineer.",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 77,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 4850,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "ETL",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 4851,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "ELT",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 4852,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Integration",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 4853,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Warehouse",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 4854,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "OLTP",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 4855,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "OLAP",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 4856,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "CSV",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 4857,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Excel",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 4858,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Amazon QuickSight",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 4859,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "SSRS",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 4860,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Stored Procedures",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 4861,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Functions",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 4862,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Tables",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 4863,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Triggers",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 4864,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Performance Tuning",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 4865,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Job Scheduling",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
API 2 — extract-details
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      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 271,
      "existing_alias_text": "SQL",
      "input_term": "SQL",
      "matched_canonical": {
        "category_id": 6,
        "display_name": "SQL",
        "id": 101,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "sql",
        "sub_category_id": 97,
        "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": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 2014,
      "existing_alias_text": "RDBMS",
      "input_term": "RDBMS",
      "matched_canonical": {
        "category_id": 3,
        "display_name": "RDBMS",
        "id": 1355,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "rdbms",
        "sub_category_id": 1023,
        "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": 1989,
      "existing_alias_text": "NoSQL",
      "input_term": "NoSQL",
      "matched_canonical": {
        "category_id": 2,
        "display_name": "NoSQL",
        "id": 1346,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "nosql",
        "sub_category_id": 1019,
        "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": 3018,
      "existing_alias_text": "JSON",
      "input_term": "JSON",
      "matched_canonical": {
        "category_id": 4,
        "display_name": "JSON",
        "id": 1984,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "STANDARD",
        "slug": "json",
        "sub_category_id": 1457,
        "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": 2600,
      "existing_alias_text": "XML",
      "input_term": "XML",
      "matched_canonical": {
        "category_id": 4,
        "display_name": "XML",
        "id": 1636,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "STANDARD",
        "slug": "xml",
        "sub_category_id": 689,
        "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": 360,
      "existing_alias_text": "Power BI",
      "input_term": "Power BI",
      "matched_canonical": {
        "category_id": 9,
        "display_name": "Power BI",
        "id": 151,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "power-bi",
        "sub_category_id": 111,
        "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": 4593,
      "existing_alias_text": "Views",
      "input_term": "Views",
      "matched_canonical": {
        "category_id": 5,
        "display_name": "Views",
        "id": 3116,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "FRAMEWORK",
        "slug": "views",
        "sub_category_id": 2424,
        "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": 2312,
      "existing_alias_text": "indexes",
      "input_term": "Indexes",
      "matched_canonical": {
        "category_id": 2,
        "display_name": "Indexes",
        "id": 1428,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "indexes",
        "sub_category_id": 2477,
        "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": 369,
      "existing_alias_text": "Query optimization",
      "input_term": "Query Optimization",
      "matched_canonical": {
        "category_id": 2,
        "display_name": "query optimization",
        "id": 160,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "query-optimization",
        "sub_category_id": 679,
        "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": 5584,
      "existing_alias_text": "Query Tuning",
      "input_term": "Performance Tuning",
      "matched_canonical": {
        "category_id": 2,
        "display_name": "query tuning",
        "id": 3553,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "query-tuning",
        "sub_category_id": 3067,
        "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": 2518,
      "existing_alias_text": "Cloud",
      "input_term": "Cloud",
      "matched_canonical": {
        "category_id": 37,
        "display_name": "Cloud",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "cloud",
        "sub_category_id": 1177,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    }
  ],
  "candidate_roles": [
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      "rationale": null,
      "role_archetype": null,
      "slug": "pega-developer",
      "source": "db"
    },
    {
      "display_name": "Data Engineer",
      "id": 2,
      "rationale": null,
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      "slug": "data-engineer",
      "source": "db"
    },
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      "display_name": "Cloud Security Engineer",
      "id": 23,
      "rationale": null,
      "role_archetype": null,
      "slug": "cloud-security-engineer",
      "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"
    },
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      "display_name": "Fullstack Developer",
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      "slug": "full-stack-engineer",
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      "display_name": "Cyber Security Engineer",
      "id": 5,
      "rationale": null,
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      "slug": "cybersecurity-engineer",
      "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",
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    },
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      "display_name": "AR/VR Engineer",
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      "rationale": null,
      "role_archetype": null,
      "slug": "ar-vr-engineer",
      "source": "db"
    },
    {
      "display_name": "Python Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "python-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Angular Frontend Developer",
      "id": 90,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "angular-frontend-developer",
      "source": "db"
    },
    {
      "display_name": "Frontend Developer",
      "id": 7,
      "rationale": null,
      "role_archetype": null,
      "slug": "frontend-engineer",
      "source": "db"
    },
    {
      "display_name": "React Frontend Developer",
      "id": 89,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "react-frontend-developer",
      "source": "db"
    },
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      "display_name": "Svelte Frontend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "svelte-frontend-developer",
      "source": "db"
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    {
      "display_name": "Vue Frontend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "vue-frontend-developer",
      "source": "db"
    },
    {
      "display_name": "Web Developer",
      "id": 25,
      "rationale": null,
      "role_archetype": null,
      "slug": "web-developer",
      "source": "db"
    },
    {
      "display_name": ".NET Backend Developer",
      "id": 83,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "dotnet-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Go Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "go-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Kotlin Backend Developer",
      "id": 84,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "kotlin-server-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Node.js Backend Developer",
      "id": 82,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "node-backend-developer",
      "source": "db"
    },
    {
      "display_name": "PHP Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "php-backend-developer",
      "source": "db"
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "ruby-backend-developer",
      "source": "db"
    },
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      "display_name": "Scala Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "scala-backend-developer",
      "source": "db"
    },
    {
      "display_name": "Drupal Dev",
      "id": 228,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "drupal-dev",
      "source": "db"
    },
    {
      "display_name": "DevOps Engineer",
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      "rationale": null,
      "role_archetype": null,
      "slug": "devops-engineer",
      "source": "db"
    },
    {
      "display_name": "Java Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "java-backend-developer",
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  ],
  "chosen_role": {
    "display_name": "Data Engineer",
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    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on end-to-end data integration, ETL/ELT pipelines, DWH development, SQL/database tuning, and cloud/Python work, which best fits a Data Engineer.",
    "role_archetype": null,
    "slug": "data-engineer",
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  "dimensions": [
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Programming languages and domain-specific languages used in Pega development.",
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        "source": "db"
      },
      "input_skill": "SQL",
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      "roles_from_db": [
        {
          "display_name": "Pega Developer",
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          "slug": "pega-developer",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Programming Languages for Data Work",
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        "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.",
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        "source": "db"
      },
      "input_skill": "SQL",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
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          "rationale": null,
          "role_archetype": null,
          "slug": "data-engineer",
          "source": "db"
        }
      ]
    },
    {
      "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.",
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        "source": "db"
      },
      "input_skill": "Python",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Cloud Security Engineer",
          "id": 23,
          "rationale": null,
          "role_archetype": null,
          "slug": "cloud-security-engineer",
          "source": "db"
        }
      ]
    },
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            "rationale": "Techniques for improving the speed, reliability, and cost efficiency of data workloads. This includes query tuning, partitioning, file sizing, compute right-sizing, and workload management.",
            "slug": "performance-and-cost-optimization",
            "source": "db"
          },
          "input_skill": "Query Optimization",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Performance and Scalability Tuning",
            "id": 11,
            "rationale": "Techniques for improving throughput, latency, and resource efficiency in PHP backend services. This includes profiling, query optimization, concurrency limits, memory use, and bottleneck analysis.",
            "slug": "performance-and-scalability-tuning",
            "source": "db"
          },
          "input_skill": "Query Optimization",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": ".NET Backend Developer",
              "id": 83,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "dotnet-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Backend Developer",
              "id": 1,
              "rationale": null,
              "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
              "slug": "backend-engineer",
              "source": "db"
            },
            {
              "display_name": "Node.js Backend Developer",
              "id": 82,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "node-backend-developer",
              "source": "db"
            },
            {
              "display_name": "PHP Backend Developer",
              "id": 86,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "php-backend-developer",
              "source": "db"
            },
            {
              "display_name": "Python Backend Developer",
              "id": 80,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "python-backend-developer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Query Optimization",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "query tuning",
          "alias_type": "CANONICAL",
          "id": 5119,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Query Tuning",
          "alias_type": "CANONICAL",
          "id": 5584,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 2,
        "display_name": "query tuning",
        "id": 3553,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "query-tuning",
        "sub_category_id": 3067,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "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"
          },
          "input_skill": "Performance Tuning",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": ".NET Backend Developer",
              "id": 83,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "dotnet-backend-developer",
              "source": "db"
            },
            {
              "display_name": "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"
            }
          ]
        }
      ],
      "input_skill": "Performance Tuning",
      "matched_via": "embedding_alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Job Scheduling",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "PRACTICE",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "job-scheduling",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Cloud",
          "alias_type": "CANONICAL",
          "id": 2518,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 37,
        "display_name": "Cloud",
        "id": 1572,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "cloud",
        "sub_category_id": 1177,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "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"
          },
          "input_skill": "Cloud",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": ".NET Backend Developer",
              "id": 83,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "dotnet-backend-developer",
              "source": "db"
            },
            {
              "display_name": "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"
            }
          ]
        }
      ],
      "input_skill": "Cloud",
      "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": [
    "ETL",
    "ELT",
    "Data Integration",
    "Data Warehouse",
    "OLTP",
    "OLAP",
    "CSV",
    "Excel",
    "Amazon QuickSight",
    "SSRS",
    "Stored Procedures",
    "Functions",
    "Tables",
    "Triggers",
    "Job Scheduling"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on end-to-end data integration, ETL/ELT pipelines, DWH development, SQL/database tuning, and cloud/Python work, which best fits a Data Engineer.",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "ETL",
      "tag": "new"
    },
    {
      "skill": "ELT",
      "tag": "new"
    },
    {
      "skill": "Data Integration",
      "tag": "new"
    },
    {
      "skill": "Data Warehouse",
      "tag": "new"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "OLTP",
      "tag": "new"
    },
    {
      "skill": "OLAP",
      "tag": "new"
    },
    {
      "skill": "RDBMS",
      "tag": "in_db"
    },
    {
      "skill": "NoSQL",
      "tag": "in_db"
    },
    {
      "skill": "JSON",
      "tag": "in_db"
    },
    {
      "skill": "XML",
      "tag": "in_db"
    },
    {
      "skill": "CSV",
      "tag": "new"
    },
    {
      "skill": "Excel",
      "tag": "new"
    },
    {
      "skill": "Power BI",
      "tag": "in_db"
    },
    {
      "skill": "Amazon QuickSight",
      "tag": "new"
    },
    {
      "skill": "SSRS",
      "tag": "new"
    },
    {
      "skill": "Stored Procedures",
      "tag": "new"
    },
    {
      "skill": "Functions",
      "tag": "new"
    },
    {
      "skill": "Tables",
      "tag": "new"
    },
    {
      "skill": "Views",
      "tag": "in_db"
    },
    {
      "skill": "Triggers",
      "tag": "new"
    },
    {
      "skill": "Indexes",
      "tag": "in_db"
    },
    {
      "skill": "Query Optimization",
      "tag": "in_db"
    },
    {
      "skill": "Performance Tuning",
      "tag": "in_db"
    },
    {
      "skill": "Job Scheduling",
      "tag": "new"
    },
    {
      "skill": "Cloud",
      "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": "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": "Cloud Security Scripting \u0026 DSL Languages",
          "id": 248,
          "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
          "slug": "cloud-security-scripting-dsl-languages",
          "source": "db"
        },
        "dimension_id": 248,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages",
          "id": 1,
          "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
          "slug": "programming-languages",
          "source": "db"
        },
        "dimension_id": 1,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages and Scripting",
          "id": 59,
          "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
          "slug": "programming-languages-and-scripting",
          "source": "db"
        },
        "dimension_id": 59,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cyber Security Engineer",
            "id": 5,
            "rationale": null,
            "role_archetype": null,
            "slug": "cybersecurity-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for Data Work",
          "id": 21,
          "rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
          "slug": "programming-languages-for-data-work",
          "source": "db"
        },
        "dimension_id": 21,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for ML Systems",
          "id": 39,
          "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
          "slug": "programming-languages-for-ml-systems",
          "source": "db"
        },
        "dimension_id": 39,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for XR",
          "id": 97,
          "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
          "slug": "programming-languages-for-xr",
          "source": "db"
        },
        "dimension_id": 97,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AR/VR Engineer",
            "id": 8,
            "rationale": null,
            "role_archetype": null,
            "slug": "ar-vr-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
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            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Cloud 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": "Cloud",
        "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": 1572,
        "skill_tag": "in_db",
        "skipped_reason": null
      }
    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 1
  },
  "planner_output": null,
  "run_id": "785fe599-c02a-4bea-b58b-4fd37285990e"
}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

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