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Pipeline run

da69246c-dd06-4d38-88d5-3fbf6533383f

Pipeline LLM cost (USD)
API 1: $0.0078 API 2: $0.0003 API 3: $0.0000 Total: $0.0081

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work · Data Integration & Data Warehousing
Designs and builds Informatica PowerCenter data integration/warehouse flows end to end, from landing and staging through ODS, marts, and consumption. Also gathers requirements, leads development/testing, and coordinates offshore teams, vendors, and client status updates.
"hands on end to end expertise in multiple implementations of data integration and data management from landing, staging, operational data store to data marts and consumption"
Tech stack maturity
Mainstream Legacy
The combination of Informatica and SQL for an ETL/ELT Developer is a common enterprise data integration stack, indicating established mainstream legacy technology.
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 (12)
Informatica Informatica PowerCenter SQL Data Integration Data Warehousing Data Architecture Database Design Data Management Operational Data Store Data Marts Waterfall Agile
Skill cluster (1 dimension groups, role-scoped)
Cross-cutting / unaligned
Informatica Informatica PowerCenter SQL Data Integration Data Warehousing Data Architecture Database Design Data Management Operational Data Store Data Marts Waterfall Agile
Show KRA description ↓
Required Skills & Experience: Requires BA/BS in Mathematics, Computer Science, Business Administration, or Analytics related field and related experience in data integration and data warehousing 5 years experience designing and developing Informatica mappings with strong Informatica Power Center experience Strong data architecture and database design and development skills Understand the deployment groups within Informatica Resource will use hands on end to end expertise in multiple implementations of data integration and data management from landing, staging, operational data store to data marts and consumption. Resource will have hands on expertise with SQL. Resource will help to gather requirements, form the design and lead in the development and testing as required to build out the solution Resource will work with the clients project management structure as needed to ensure the project is lead in the proper manner. Strong ability to lead offshore teams in a production support manner. Resource must have solid demonstratable Informatica on prem data integration engineering experience to focus mainly on working with client’s team and multiple vendors on building out the solution. Solid ability to manage client expectations and offshore team management to ensure all tasks are executed as expected and communicate daily status as needed to client and onshore team Full lifecycle experience in waterfall and agile development methodologies Intelligent but practical; you want to get things done and love simplicity Excellent presenter, influencer

Signals

Skill data-engineer
0.17
Alias
KRA data-engineer
0.55

Post-classification

Centroidupdated · n=21
Alias collision log
New-role queue
New skills captured9
New KRA capturedyes

Captured for admin review

Informatica PowerCenter primary ETL / ELT Developer pending
Data Integration primary ETL / ELT Developer pending
Data Warehousing primary ETL / ELT Developer pending
Data Architecture primary ETL / ELT Developer pending
Database Design primary ETL / ELT Developer pending
Data Management primary ETL / ELT Developer pending
Operational Data Store primary ETL / ELT Developer pending
Data Marts primary ETL / ELT Developer pending
Waterfall primary ETL / ELT Developer pending
R&R fragment (sim 0.00) ETL / ELT Developer pending

Required Skills & Experience: Requires BA/BS in Mathematics, Computer Science, Business Administration, or Analytics related field and related experience in data integration and data warehousing 5 yea…

Status: completed Created: 2026-05-27T17:40:43.196016Z Updated: 2026-06-07T08:00:59.810465Z API 3 duration: 4561 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

ETL / ELT Developer

domain · Data Engineering & Analytics CASE DOMAIN

slug: etl-elt-developer · id: 50 · source: db

Domain=Data Engineering & Analytics; The JD is centered on Informatica PowerCenter-based ETL/data integration implementation, which best matches ETL/ELT Developer.

Matched skills

Informatica mappingsInformatica Power Centerdata architecturedatabase designdeployment groupsdata integrationdata warehousinglandingstagingoperational data storedata martsSQLwaterfallagile

Matched dimensions

ETL and data integration developmentData warehousing implementationData architecture and database designRequirements gathering and solution designProduction support and offshore team leadershipClient/vendor coordination and project communication

Matched KRAs

designing and developing Informatica mappingsuse hands on end to end expertisehelp to gather requirementslead in the development and testingwork with the clients project management structurelead offshore teams in a production support mannermanage client expectations and offshore team managementcommunicate daily status as needed

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
2
Skipped

Job description

Job Description

Mandatory Skills

Informatica,Sql

Experience In Years

2 to 4 years

Location

Hyderabad

Roles & Responsibilities

Required Skills & Experience:
 Requires BA/BS in Mathematics, Computer Science, Business Administration, or Analytics related field and related experience in data integration and data warehousing 5 years experience designing and developing Informatica mappings with strong Informatica Power Center experience Strong data architecture and database design and development skills Understand the deployment groups within Informatica Resource will use hands on end to end expertise in multiple implementations of data integration and data management from landing, staging, operational data store to data marts and consumption. Resource will have hands on expertise with SQL. Resource will help to gather requirements, form the design and lead in the development and testing as required to build out the solution Resource will work with the clients project management structure as needed to ensure the project is lead in the proper manner. Strong ability to lead offshore teams in a production support manner. Resource must have solid demonstratable Informatica on prem data integration engineering experience to focus mainly on working with client’s team and multiple vendors on building out the solution. Solid ability to manage client expectations and offshore team management to ensure all tasks are executed as expected and communicate daily status as needed to client and onshore team Full lifecycle experience in waterfall and agile development methodologies Intelligent but practical; you want to get things done and love simplicity Excellent presenter, influencer

Skills from this JD

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

Informatica Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Informatica id=117 · informatica

Aliases — catalog

  • Informatica (CANONICAL) primary

Context tags (catalog)

CDC Cloud Data Integration ELT ETL IICS PowerCenter data integration data quality data warehousing lookup transformation mapping repository session source qualifier workflow

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Data Integration Platform
Vendor
Informatica
License
proprietary
Year introduced
1993
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Informatica appears frequently in enterprise data-integration and ETL job postings, especially alongside cloud migration and MDM roles; it remains a common hiring keyword rather than a sunset technology.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
114
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • ETL and ELT Tooling Catalog dimension db id 24

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Informatica PowerCenter 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
TOOL
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 & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • 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 & DSLs
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 skipped (dimension not under chosen role)
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
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Warehousing 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 Architecture 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
Database Design Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: schema design id=19 · schema-design

Aliases — catalog

  • schema design (CANONICAL) primary
  • Schema Design (CANONICAL)

Context tags (catalog)

ACID DDL ER modeling ERD NoSQL SQL cardinality constraints data governance data integrity data lineage data model data modeling data normalization data types data warehouse database design database normalization database optimization database schema denormalization dimensional modeling entity relationship entity-relationship entity-relationship diagram foreign key foreign keys indexes indexing metadata management normalization primary key primary keys query optimization relational relational databases relational model relational schema schema evolution schema migration snowflake schema star schema

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Database Schema Design
Confidence
0.84
Version strategy
NOT_APPLICABLE

Maturity reasoning: Schema design is a standard requirement in backend/data JDs and appears across SQL, data engineering, and SaaS roles; it’s a core interview topic rather than a niche specialty.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
2479
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Relational Data Modeling Catalog dimension db id 216

    Library dimension (catalog)

    Roles linked in library: Fullstack Developer, Fullstack Developer, PHP Backend Developer

  • Relational Database Design Catalog dimension db id 4

    Library dimension (catalog)

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

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Relational Data Modeling
relational-data-modeling
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Relational Database Design
relational-database-design
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
Data Management 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
Operational Data Store 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 Marts 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
Waterfall 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
Project Management
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Agile Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Agile id=520 · agile

Aliases — catalog

  • Agile (CANONICAL) primary

Context tags (catalog)

Kanban SAFe Scrum backlog backlog grooming burndown burndown chart continuous delivery continuous improvement cross-functional daily standup epics incremental development iteration iteration planning lean product backlog product owner retrospective sprint sprint planning stand-up story points user stories velocity

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Agile
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Agile appears in a large share of software job descriptions and is a standard hiring-pipeline requirement; Scrum/Kanban are commonly listed alongside it, showing broad market adoption.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
3594
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Software Concepts, Patterns & Practices Catalog dimension db id 478

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

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
Informatica in_db
ETL and ELT Tooling
etl-and-elt-tooling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
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 & DSLs
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 skipped (dimension not under chosen role)
Database Design new
Relational Data Modeling
relational-data-modeling
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Database Design new
Relational Database Design
relational-database-design
Skipped — no persistable v3 meta for new skill skill_not_in_db_v3_proposed
Agile in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile in_db
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Informatica PowerCenter | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Data Integration | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Data Warehousing | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Data Architecture | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Data Management | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Operational Data Store | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Data Marts | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Waterfall | type=Project Management subtype=general nature=PRACTICE lifespan=MULTI_YEAR
dimension_skill_link_proposed Database Design ↔ Relational Data Modeling
dimension_skill_link_proposed Database Design ↔ Relational Database Design
nano JD Parser — gpt-4.1-nano click to toggle
Experience2 to 4 years
DomainOther
Location Hyderabad, India
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
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  "education": [
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      "level": "Bachelor\u0027s",
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      "requirement": "required"
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  "experience": {
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  "roles_and_responsibilities": [
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      "bullet_count": 0,
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      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "Required Skills \u0026 Experience: Requires",
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      },
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      "word_count": 284
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  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Informatica"
    },
    {
      "is_primary": true,
      "skill_name": "Informatica PowerCenter"
    },
    {
      "is_primary": true,
      "skill_name": "SQL"
    },
    {
      "is_primary": true,
      "skill_name": "Data Integration"
    },
    {
      "is_primary": true,
      "skill_name": "Data Warehousing"
    },
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      "skill_name": "Data Architecture"
    },
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    },
    {
      "is_primary": true,
      "skill_name": "Data Management"
    },
    {
      "is_primary": true,
      "skill_name": "Operational Data Store"
    },
    {
      "is_primary": true,
      "skill_name": "Data Marts"
    },
    {
      "is_primary": true,
      "skill_name": "Waterfall"
    },
    {
      "is_primary": true,
      "skill_name": "Agile"
    }
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  "nano_parsed": {
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  "run_id": "da69246c-dd06-4d38-88d5-3fbf6533383f",
  "stage3_signals": {
    "alias_found": false,
    "alias_match_roles": [],
    "kra_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": [
          {
            "kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
            "sentence": "Resource will use hands on end to end expertise in multiple implementations of data integration and data management from landing, staging, operational data store to data marts and consumption.",
            "similarity": 0.5749
          },
          {
            "kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
            "sentence": "Requires BA/BS in Mathematics, Computer Science, Business Administration, or Analytics related field and related experience in data integration and data warehousing",
            "similarity": 0.5494
          },
          {
            "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": "Strong data architecture and database design and development skills",
            "similarity": 0.5395
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 0.5546,
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        "total_count": null
      },
      {
        "display_name": "Fullstack Developer",
        "kra_matches": [
          {
            "kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
            "sentence": "Strong data architecture and database design and development skills",
            "similarity": 0.5422
          },
          {
            "kra_text": "Works closely with product managers and UX designers to translate requirements and wireframes into working software features through iterative development.",
            "sentence": "Resource will help to gather requirements, form the design and lead in the development and testing as required to build out the solution",
            "similarity": 0.482
          },
          {
            "kra_text": "Works closely with product managers and UX designers to translate requirements and wireframes into working software features through iterative development.",
            "sentence": "Full lifecycle experience in waterfall and agile development methodologies",
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        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 15,
        "score": 0.4926,
        "slug": "full-stack-engineer",
        "total_count": null
      },
      {
        "display_name": "Svelte Frontend Developer",
        "kra_matches": [
          {
            "kra_text": "backend data integration",
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            "similarity": 0.4779
          },
          {
            "kra_text": "backend data integration",
            "sentence": "Strong data architecture and database design and development skills",
            "similarity": 0.4779
          },
          {
            "kra_text": "backend data integration",
            "sentence": "Requires BA/BS in Mathematics, Computer Science, Business Administration, or Analytics related field and related experience in data integration and data warehousing",
            "similarity": 0.4505
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 92,
        "score": 0.4687,
        "slug": "svelte-frontend-developer",
        "total_count": null
      },
      {
        "display_name": "Engineering Manager",
        "kra_matches": [
          {
            "kra_text": "Set team goals and delivery plans",
            "sentence": "Solid ability to manage client expectations and offshore team management to ensure all tasks are executed as expected and communicate daily status as needed to client and onshore team",
            "similarity": 0.521
          },
          {
            "kra_text": "facilitate technical and delivery decisions",
            "sentence": "Resource will help to gather requirements, form the design and lead in the development and testing as required to build out the solution",
            "similarity": 0.4431
          },
          {
            "kra_text": "facilitate technical and delivery decisions",
            "sentence": "Resource must have solid demonstratable Informatica on prem data integration engineering experience to focus mainly on working with client\u2019s team and multiple vendors on building out the solution.",
            "similarity": 0.4199
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 121,
        "score": 0.4613,
        "slug": "engineering-manager",
        "total_count": null
      },
      {
        "display_name": "Cloud Architect",
        "kra_matches": [
          {
            "kra_text": "Conducts architecture reviews, approves technical design documents, and guides engineering teams through cloud migration and modernization projects.",
            "sentence": "Strong data architecture and database design and development skills",
            "similarity": 0.4676
          },
          {
            "kra_text": "Conducts architecture reviews, approves technical design documents, and guides engineering teams through cloud migration and modernization projects.",
            "sentence": "Resource will help to gather requirements, form the design and lead in the development and testing as required to build out the solution",
            "similarity": 0.4556
          },
          {
            "kra_text": "Designs backup policies, cross-region replication, and disaster recovery runbooks to meet defined RTO and RPO targets for critical workloads.",
            "sentence": "Resource will use hands on end to end expertise in multiple implementations of data integration and data management from landing, staging, operational data store to data marts and consumption.",
            "similarity": 0.452
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 9,
        "score": 0.4584,
        "slug": "cloud-architect",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "Informatica",
          "SQL"
        ],
        "role_id": 2,
        "score": 0.1667,
        "slug": "data-engineer",
        "total_count": 12
      },
      {
        "display_name": "Engineering Manager",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "Agile",
          "SQL"
        ],
        "role_id": 121,
        "score": 0.1667,
        "slug": "engineering-manager",
        "total_count": 12
      },
      {
        "display_name": "Pega Developer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "SQL"
        ],
        "role_id": 24,
        "score": 0.0833,
        "slug": "pega-developer",
        "total_count": 12
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "DOMAIN",
    "chosen_role": {
      "display_name": "ETL / ELT Developer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 50,
      "score": 0.98,
      "slug": "etl-elt-developer",
      "total_count": null
    },
    "confidence": 0.98,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [
      "ETL and data integration development",
      "Data warehousing implementation",
      "Data architecture and database design",
      "Requirements gathering and solution design",
      "Production support and offshore team leadership",
      "Client/vendor coordination and project communication"
    ],
    "matched_kras": [
      "designing and developing Informatica mappings",
      "use hands on end to end expertise",
      "help to gather requirements",
      "lead in the development and testing",
      "work with the clients project management structure",
      "lead offshore teams in a production support manner",
      "manage client expectations and offshore team management",
      "communicate daily status as needed"
    ],
    "matched_skills": [
      "Informatica mappings",
      "Informatica Power Center",
      "data architecture",
      "database design",
      "deployment groups",
      "data integration",
      "data warehousing",
      "landing",
      "staging",
      "operational data store",
      "data marts",
      "SQL",
      "waterfall",
      "agile"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=Data Engineering \u0026 Analytics; The JD is centered on Informatica PowerCenter-based ETL/data integration implementation, which best matches ETL/ELT Developer.",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 21,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": {
      "best_kra_similarity": 0.0,
      "queue_id": 1975,
      "r_and_r_preview": "Required Skills \u0026 Experience:\nRequires BA/BS in Mathematics, Computer Science, Business Administration, or Analytics related field and related experience in data integration and data warehousing\n5 yea",
      "role_display_name": "ETL / ELT Developer",
      "role_slug": "etl-elt-developer",
      "status": "pending"
    },
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 25288,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Informatica PowerCenter",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 25289,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Data Integration",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 25290,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Data Warehousing",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 25291,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Data Architecture",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 25292,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Database Design",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 25293,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Data Management",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 25294,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Operational Data Store",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 25295,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Data Marts",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 25296,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Waterfall",
        "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_persisted": false,
      "existing_alias_id": 311,
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      "matched_canonical": {
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        "display_name": "Informatica",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PLATFORM",
        "slug": "informatica",
        "sub_category_id": 114,
        "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": 271,
      "existing_alias_text": "SQL",
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      "matched_canonical": {
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        "display_name": "SQL",
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        "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": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
      "alias_persisted": false,
      "existing_alias_id": 5581,
      "existing_alias_text": "Schema Design",
      "input_term": "Database Design",
      "matched_canonical": {
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "schema-design",
        "sub_category_id": 2479,
        "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": 868,
      "existing_alias_text": "Agile",
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      "matched_canonical": {
        "category_id": 8,
        "display_name": "Agile",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "agile",
        "sub_category_id": 3594,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    }
  ],
  "candidate_roles": [
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    },
    {
      "display_name": ".NET Backend Developer",
      "id": 83,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "dotnet-backend-developer",
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    },
    {
      "display_name": "Backend Developer",
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      "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",
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    {
      "display_name": "Kotlin Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "kotlin-server-backend-developer",
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    },
    {
      "display_name": "Node.js Backend Developer",
      "id": 82,
      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "node-backend-developer",
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    },
    {
      "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",
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    },
    {
      "display_name": "Scala Backend Developer",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "scala-backend-developer",
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  ],
  "chosen_role": {
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    "role_archetype": "Data",
    "slug": "etl-elt-developer",
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  "dimensions": [
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      },
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        {
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Pega Programming Languages \u0026 DSLs",
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        "rationale": "Programming languages and domain-specific languages used in Pega development.",
        "slug": "pega-programming-languages-dsls",
        "source": "db"
      },
      "input_skill": "SQL",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
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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",
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      "roles_from_db": [
        {
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "Relational Data Modeling",
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        "rationale": "Modeling and tuning relational persistence for backend features. PHP backend developers need this to shape schemas, indexes, transactions, and query-aware data structures that support application behavior.",
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        "source": "db"
      },
      "input_skill": "Database Design",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Fullstack Developer",
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        },
        {
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        },
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        }
      ]
    },
    {
      "dimension": {
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        "rationale": "Modeling and operating relational persistence for backend services. Includes schema design, normalization, indexing, transactions, and query tuning for operational data stores.",
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        "source": "db"
      },
      "input_skill": "Database Design",
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      "roles_from_db": [
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          "display_name": ".NET Backend Developer",
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      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
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        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "Agile",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
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        "rationale": "Champion foundational software design patterns, development methodologies, and engineering best practices.",
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  ],
  "input_final_skills": [
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  "input_llm_skills": [
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  "new_aliases_persisted": 0,
  "run_id": "da69246c-dd06-4d38-88d5-3fbf6533383f",
  "skills_detail": [
    {
      "aliases_in_db": [
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          "alias_text": "Informatica",
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      ],
      "canonical": {
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            "display_name": "ETL and ELT Tooling",
            "id": 24,
            "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
            "slug": "etl-and-elt-tooling",
            "source": "db"
          },
          "input_skill": "Informatica",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Informatica",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Informatica PowerCenter",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "TOOL",
          "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": "informatica-powercenter",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "SQL",
          "alias_type": "CANONICAL",
          "id": 271,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "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"
      },
      "dimensions": [
        {
          "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"
          },
          "input_skill": "SQL",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Pega Developer",
              "id": 24,
              "rationale": null,
              "role_archetype": null,
              "slug": "pega-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages \u0026 DSLs",
            "id": 475,
            "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
            "slug": "programming-languages-dsls",
            "source": "db"
          },
          "input_skill": "SQL",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Engineering Manager",
              "id": 121,
              "rationale": null,
              "role_archetype": null,
              "slug": "engineering-manager",
              "source": "db"
            }
          ]
        },
        {
          "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"
          },
          "input_skill": "SQL",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "SQL",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Data Integration",
      "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": "data-integration",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Data Warehousing",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "CONCEPT",
          "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": "data-warehousing",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Data Architecture",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "CONCEPT",
          "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": "data-architecture",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "schema design",
          "alias_type": "CANONICAL",
          "id": 147,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Schema Design",
          "alias_type": "CANONICAL",
          "id": 5581,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 2,
        "display_name": "schema design",
        "id": 19,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "schema-design",
        "sub_category_id": 2479,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Relational Data Modeling",
            "id": 216,
            "rationale": "Modeling and tuning relational persistence for backend features. PHP backend developers need this to shape schemas, indexes, transactions, and query-aware data structures that support application behavior.",
            "slug": "relational-data-modeling",
            "source": "db"
          },
          "input_skill": "Database Design",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Fullstack Developer",
              "id": 15,
              "rationale": null,
              "role_archetype": null,
              "slug": "full-stack-engineer",
              "source": "db"
            },
            {
              "display_name": "Fullstack Developer",
              "id": 435,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "fullstack-developer",
              "source": "db"
            },
            {
              "display_name": "PHP Backend Developer",
              "id": 86,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "php-backend-developer",
              "source": "db"
            }
          ]
        },
        {
          "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": "Database Design",
          "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": "Database Design",
      "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": "Data Management",
      "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": "data-management",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Operational Data Store",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "CONCEPT",
          "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": "operational-data-store",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Data Marts",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "CONCEPT",
          "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": "data-marts",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Waterfall",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Project Management",
          "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": "waterfall",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Agile",
          "alias_type": "CANONICAL",
          "id": 868,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "Agile",
        "id": 520,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "agile",
        "sub_category_id": 3594,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "Agile",
          "llm_role": null,
          "roles_from_db": []
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Software Concepts, Patterns \u0026 Practices",
            "id": 478,
            "rationale": "Champion foundational software design patterns, development methodologies, and engineering best practices.",
            "slug": "software-concepts-patterns-practices",
            "source": "db"
          },
          "input_skill": "Agile",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Engineering Manager",
              "id": 121,
              "rationale": null,
              "role_archetype": null,
              "slug": "engineering-manager",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Agile",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Informatica PowerCenter",
    "Data Integration",
    "Data Warehousing",
    "Data Architecture",
    "Data Management",
    "Operational Data Store",
    "Data Marts",
    "Waterfall"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "ETL / ELT Developer",
    "id": 50,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD is centered on Informatica PowerCenter-based ETL/data integration implementation, which best matches ETL/ELT Developer.",
    "role_archetype": "Data",
    "slug": "etl-elt-developer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Informatica",
      "tag": "in_db"
    },
    {
      "skill": "Informatica PowerCenter",
      "tag": "new"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "Data Integration",
      "tag": "new"
    },
    {
      "skill": "Data Warehousing",
      "tag": "new"
    },
    {
      "skill": "Data Architecture",
      "tag": "new"
    },
    {
      "skill": "Database Design",
      "tag": "in_db"
    },
    {
      "skill": "Data Management",
      "tag": "new"
    },
    {
      "skill": "Operational Data Store",
      "tag": "new"
    },
    {
      "skill": "Data Marts",
      "tag": "new"
    },
    {
      "skill": "Waterfall",
      "tag": "new"
    },
    {
      "skill": "Agile",
      "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": 50,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "ETL and ELT Tooling",
          "id": 24,
          "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
          "slug": "etl-and-elt-tooling",
          "source": "db"
        },
        "dimension_id": 24,
        "input_skill": "Informatica",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 117,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 50,
        "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": 50,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages \u0026 DSLs",
          "id": 475,
          "rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
          "slug": "programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 475,
        "input_skill": "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": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 50,
        "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": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
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