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Pipeline run

801b594a-6d58-485e-b531-6c4524cf7a55

Pipeline LLM cost (USD)
API 1: $0.0079 API 2: $0.0004 API 3: $0.0000 Total: $0.0082

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work no kras
Vague JD — no KRAs present to derive a specific nature of work.
Tech stack maturity
Mainstream Legacy
Informatica and SQL are common enterprise ETL technologies typically associated with long-established, widely used data integration 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 (13)
ETL Informatica DataStage SQL Database Packages Stored Procedures Functions Workflows Mappings Code Review Testing Performance Tuning Automation
Skill cluster (1 dimension groups, role-scoped)
Cross-cutting / unaligned
ETL Informatica DataStage SQL Database Packages Stored Procedures Functions Workflows Mappings Code Review Testing Performance Tuning Automation

Signals

Skill data-engineer
0.22
Alias
KRA flutter-developer
0.56

Post-classification

Centroidupdated · n=9
Alias collision log
New-role queue
New skills captured10
New KRA captured

Captured for admin review

ETL primary ETL / ELT Developer pending
DataStage primary ETL / ELT Developer pending
Database Packages primary ETL / ELT Developer pending
Stored Procedures primary ETL / ELT Developer pending
Functions primary ETL / ELT Developer pending
Workflows primary ETL / ELT Developer pending
Mappings primary ETL / ELT Developer pending
Testing ETL / ELT Developer pending
Performance Tuning ETL / ELT Developer pending
Automation ETL / ELT Developer pending
Status: completed Created: 2026-05-27T15:20:54.376492Z Updated: 2026-06-12T16:35:17.126414Z API 3 duration: 11688 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 building and maintaining ETL solutions, specifically Informatica and Datastage workflows/mappings, which best matches an ETL / ELT Developer.

Matched skills

ETLInformaticaDatastageworkflowsmappingsdatabase Packagesproceduresfunctionsperformance tuningroot cause analysiscode reviewtesting

Matched dimensions

ETL Solution DesignData Conversion StrategyWorkflow and Mapping DevelopmentPerformance TuningTechnical Requirements TranslationTesting and Deployment SupportProcess and Automation Improvement

Matched KRAs

Design ETL solutions and data conversion strategiesCreate an end-to-end solution for ETL transformational jobsDevelop, maintain, and enhance Informatica Mappings, Work-flows, and processesSupport proper functioning and performance tuningTranslate business requirements into functional/technical specificationsDesigning and coding Datastage packagesPrepare root cause analysis documentsConduct code review, and test and tune the developed jobsProvide inputs to testing strategy, configuration, deployment

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

Note:- Minimum 5 years of experience required


About Company:
Truelancer Enterprise gig work platform where we take up on-the-ground or digital recurring work from enterprises and get it done through a million gig workers across 200+ cities in India. Our objective is to simplify the execution of different complex processes involving managing teams of multiple people at different hierarchical levels and enable millions of Gig workers to perform their task efficiently.


Skills:-
• ETL
Job Description


• No less than 4 years IT experience in Design ETL solutions and data conversion strategies and solutions for multiple disparate systems
• Create an end-to-end solution for ETL transformational jobs that involve writing workflows and mappings, and creating database Packages, procedures and functions
• Develop, maintain, and enhance Informatica Mappings, Work-flows, and processes
• Support proper functioning and performance tuning.
• Translate business requirements into functional/technical specifications
• Designing and coding Datastage packages
• Prepare root cause analysis documents, conduct code review, and test and tune the developed jobs
• Provide inputs to testing strategy, configuration, deployment, hardware/software requirement
• Identify avenues to improve project delivery parameters (eg productivity, efficiency, process, security etc) by leveraging tools, automation
• Understand various technical tools used in the project (third party homegrown) to improve efficiency , productivity.


Location- Remote

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
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)
DataStage 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
ETL Tools
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)
Database Packages 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
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Stored Procedures 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
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Functions 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
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Workflows 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
Automation Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Mappings 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
Code Review Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Code Review id=516 · code-review

Aliases — catalog

  • Code Review (CANONICAL)

Context tags (catalog)

Bitbucket GitHub GitLab PR review approval workflow branch protection code quality diff inline comments linting merge request pair programming pull request review checklist static analysis

Stored enrichment (catalog DB)

Category
SoftSkill
Sub-category
Code Review
Confidence
0.96
Version strategy
NOT_APPLICABLE

Maturity reasoning: Code review is a standard hiring-pipeline requirement in engineering JDs and is built into major platforms like GitHub/GitLab pull-request workflows, indicating broad adoption.

Skill profile (library / DB)

Skill nature
PRACTICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
58
Sub-category id
364
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)
Testing 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
Testing Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
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
Automation 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
Automation Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED

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)
Code Review in_db
React Frontend Development
d_init_01
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

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 DataStage | type=Data Engineering Tools subtype=ETL Tools nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Database Packages | type=Databases subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Stored Procedures | type=Databases subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed Functions | type=Databases subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed Workflows | type=Automation Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Mappings | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Testing | type=Testing Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Automation | type=Automation 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
JD type fail
Show raw JSON
{
  "JD_type": "fail",
  "archetype_override_applied": true,
  "archetype_override_matched_skills": [
    "Informatica",
    "Code Review",
    "Location",
    "Task",
    "workers",
    "root cause analysis"
  ],
  "role_archetype": "Engineering"
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "ETL"
    },
    {
      "is_primary": true,
      "skill_name": "Informatica"
    },
    {
      "is_primary": true,
      "skill_name": "DataStage"
    },
    {
      "is_primary": true,
      "skill_name": "SQL"
    },
    {
      "is_primary": true,
      "skill_name": "Database Packages"
    },
    {
      "is_primary": true,
      "skill_name": "Stored Procedures"
    },
    {
      "is_primary": true,
      "skill_name": "Functions"
    },
    {
      "is_primary": true,
      "skill_name": "Workflows"
    },
    {
      "is_primary": true,
      "skill_name": "Mappings"
    },
    {
      "is_primary": false,
      "skill_name": "Code Review"
    },
    {
      "is_primary": false,
      "skill_name": "Testing"
    },
    {
      "is_primary": false,
      "skill_name": "Performance Tuning"
    },
    {
      "is_primary": false,
      "skill_name": "Automation"
    }
  ],
  "jd_role": null,
  "nano_parsed": {
    "JD_type": "fail",
    "archetype_override_applied": true,
    "archetype_override_matched_skills": [
      "Informatica",
      "Code Review",
      "Location",
      "Task",
      "workers",
      "root cause analysis"
    ],
    "role_archetype": "Engineering"
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "801b594a-6d58-485e-b531-6c4524cf7a55",
  "stage3_signals": {
    "alias_found": false,
    "alias_match_roles": [],
    "kra_match_roles": [
      {
        "display_name": "Flutter Developer",
        "kra_matches": [
          {
            "kra_text": "translate product and design requirements",
            "sentence": "Translate business requirements into functional/technical specifications",
            "similarity": 0.7176
          },
          {
            "kra_text": "optimize responsiveness and performance",
            "sentence": "Support proper functioning and performance tuning.",
            "similarity": 0.5427
          },
          {
            "kra_text": "collaborate with design, product, and backend teams",
            "sentence": "Prepare root cause analysis documents, conduct code review, and test and tune the developed jobs",
            "similarity": 0.4216
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 74,
        "score": 0.5606,
        "slug": "flutter-developer",
        "total_count": null
      },
      {
        "display_name": "Scala Backend Developer",
        "kra_matches": [
          {
            "kra_text": "performance and reliability tuning",
            "sentence": "Support proper functioning and performance tuning.",
            "similarity": 0.6528
          },
          {
            "kra_text": "performance and reliability tuning",
            "sentence": "Prepare root cause analysis documents, conduct code review, and test and tune the developed jobs",
            "similarity": 0.4925
          },
          {
            "kra_text": "backend workflow orchestration",
            "sentence": "Our objective is to simplify the execution of different complex processes involving managing teams of multiple people at different hierarchical levels and enable millions of Gig workers to perform their task efficiently.",
            "similarity": 0.4704
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 87,
        "score": 0.5386,
        "slug": "scala-backend-developer",
        "total_count": null
      },
      {
        "display_name": "Go Backend Developer",
        "kra_matches": [
          {
            "kra_text": "performance tuning and resource efficiency",
            "sentence": "Support proper functioning and performance tuning.",
            "similarity": 0.5925
          },
          {
            "kra_text": "code review and testing support",
            "sentence": "Prepare root cause analysis documents, conduct code review, and test and tune the developed jobs",
            "similarity": 0.5718
          },
          {
            "kra_text": "performance tuning and resource efficiency",
            "sentence": "Understand various technical tools used in the project (third party homegrown) to improve efficiency , productivity.",
            "similarity": 0.4428
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 81,
        "score": 0.5357,
        "slug": "go-backend-developer",
        "total_count": null
      },
      {
        "display_name": "Kotlin Backend Developer",
        "kra_matches": [
          {
            "kra_text": "performance and reliability tuning",
            "sentence": "Support proper functioning and performance tuning.",
            "similarity": 0.6528
          },
          {
            "kra_text": "performance and reliability tuning",
            "sentence": "Prepare root cause analysis documents, conduct code review, and test and tune the developed jobs",
            "similarity": 0.4925
          },
          {
            "kra_text": "Backend business logic implementation",
            "sentence": "Translate business requirements into functional/technical specifications",
            "similarity": 0.439
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 84,
        "score": 0.5281,
        "slug": "kotlin-server-backend-developer",
        "total_count": null
      },
      {
        "display_name": "Java Backend Developer",
        "kra_matches": [
          {
            "kra_text": "backend performance tuning",
            "sentence": "Support proper functioning and performance tuning.",
            "similarity": 0.6262
          },
          {
            "kra_text": "code refactoring and defect fixes",
            "sentence": "Prepare root cause analysis documents, conduct code review, and test and tune the developed jobs",
            "similarity": 0.5203
          },
          {
            "kra_text": "asynchronous job processing",
            "sentence": "Our objective is to simplify the execution of different complex processes involving managing teams of multiple people at different hierarchical levels and enable millions of Gig workers to perform their task efficiently.",
            "similarity": 0.4233
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 79,
        "score": 0.5233,
        "slug": "java-backend-developer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "Informatica",
          "SQL"
        ],
        "role_id": 2,
        "score": 0.2222,
        "slug": "data-engineer",
        "total_count": 9
      },
      {
        "display_name": "Pega Developer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "SQL"
        ],
        "role_id": 24,
        "score": 0.1111,
        "slug": "pega-developer",
        "total_count": 9
      },
      {
        "display_name": "Engineering Manager",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "SQL"
        ],
        "role_id": 121,
        "score": 0.1111,
        "slug": "engineering-manager",
        "total_count": 9
      }
    ]
  },
  "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 Solution Design",
      "Data Conversion Strategy",
      "Workflow and Mapping Development",
      "Performance Tuning",
      "Technical Requirements Translation",
      "Testing and Deployment Support",
      "Process and Automation Improvement"
    ],
    "matched_kras": [
      "Design ETL solutions and data conversion strategies",
      "Create an end-to-end solution for ETL transformational jobs",
      "Develop, maintain, and enhance Informatica Mappings, Work-flows, and processes",
      "Support proper functioning and performance tuning",
      "Translate business requirements into functional/technical specifications",
      "Designing and coding Datastage packages",
      "Prepare root cause analysis documents",
      "Conduct code review, and test and tune the developed jobs",
      "Provide inputs to testing strategy, configuration, deployment"
    ],
    "matched_skills": [
      "ETL",
      "Informatica",
      "Datastage",
      "workflows",
      "mappings",
      "database Packages",
      "procedures",
      "functions",
      "performance tuning",
      "root cause analysis",
      "code review",
      "testing"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=Data Engineering \u0026 Analytics; The JD is centered on building and maintaining ETL solutions, specifically Informatica and Datastage workflows/mappings, which best matches an ETL / ELT Developer.",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 9,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 13837,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "ETL",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13838,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "DataStage",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13839,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Database Packages",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13840,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Stored Procedures",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13841,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Functions",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13842,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Workflows",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13843,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Mappings",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 13844,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Testing",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 13845,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Performance Tuning",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 13846,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Automation",
        "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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        "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",
      "input_term": "SQL",
      "matched_canonical": {
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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": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 864,
      "existing_alias_text": "Code Review",
      "input_term": "Code Review",
      "matched_canonical": {
        "category_id": 58,
        "display_name": "Code Review",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PRACTICE",
        "slug": "code-review",
        "sub_category_id": 364,
        "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",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
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        "sub_category_id": 3067,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "embedding_alias"
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  ],
  "candidate_roles": [
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      "display_name": "Data Engineer",
      "id": 2,
      "rationale": null,
      "role_archetype": null,
      "slug": "data-engineer",
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    },
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      "display_name": "Pega Developer",
      "id": 24,
      "rationale": null,
      "role_archetype": null,
      "slug": "pega-developer",
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      "slug": "engineering-manager",
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      "rationale": null,
      "role_archetype": "Engineering",
      "slug": "kotlin-server-backend-developer",
      "source": "db"
    },
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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",
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    },
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      "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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    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD is centered on building and maintaining ETL solutions, specifically Informatica and Datastage workflows/mappings, which best matches an ETL / ELT Developer.",
    "role_archetype": "Data",
    "slug": "etl-elt-developer",
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        "source": "db"
      },
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      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "Data Engineer",
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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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        {
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      ]
    },
    {
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      ]
    },
    {
      "dimension": {
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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": "Code Review",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "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"
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  "new_aliases_persisted": 0,
  "run_id": "801b594a-6d58-485e-b531-6c4524cf7a55",
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      },
      "source_tag": "llm",
      "was_in_llm_skills": true
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    {
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      ],
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          ]
        }
      ],
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        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "workflows",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Mappings",
      "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": "mappings",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Code Review",
          "alias_type": "CANONICAL",
          "id": 864,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 58,
        "display_name": "Code Review",
        "id": 516,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PRACTICE",
        "slug": "code-review",
        "sub_category_id": 364,
        "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": "Code Review",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "Code Review",
      "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": "Testing",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Testing 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": "testing",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "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": "Automation",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Automation 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": "automation",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "ETL",
    "DataStage",
    "Database Packages",
    "Stored Procedures",
    "Functions",
    "Workflows",
    "Mappings",
    "Testing",
    "Automation"
  ]
}
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 building and maintaining ETL solutions, specifically Informatica and Datastage workflows/mappings, which best matches an ETL / ELT Developer.",
    "role_archetype": "Data",
    "slug": "etl-elt-developer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "ETL",
      "tag": "new"
    },
    {
      "skill": "Informatica",
      "tag": "in_db"
    },
    {
      "skill": "DataStage",
      "tag": "new"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "Database Packages",
      "tag": "new"
    },
    {
      "skill": "Stored Procedures",
      "tag": "new"
    },
    {
      "skill": "Functions",
      "tag": "new"
    },
    {
      "skill": "Workflows",
      "tag": "new"
    },
    {
      "skill": "Mappings",
      "tag": "new"
    },
    {
      "skill": "Code Review",
      "tag": "in_db"
    },
    {
      "skill": "Testing",
      "tag": "new"
    },
    {
      "skill": "Performance Tuning",
      "tag": "in_db"
    },
    {
      "skill": "Automation",
      "tag": "new"
    }
  ],
  "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,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 50,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Code Review",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 516,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 50,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Relational Database Design",
          "id": 4,
          "rationale": "Modeling and operating relational persistence for backend services. Includes schema design, normalization, indexing, transactions, and query tuning for operational data stores.",
          "slug": "relational-database-design",
          "source": "db"
        },
        "dimension_id": 4,
        "input_skill": "Performance Tuning",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Skipped \u2014 no persistable v3 meta for new skill",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": ".NET Backend Developer",
            "id": 83,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "dotnet-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Kotlin Backend Developer",
            "id": 84,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "kotlin-server-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Ruby Backend Developer",
            "id": 85,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "ruby-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": false,
        "skill_id": null,
        "skill_tag": "new",
        "skipped_reason": "skill_not_in_db_v3_proposed"
      }
    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 1
  },
  "planner_output": null,
  "run_id": "801b594a-6d58-485e-b531-6c4524cf7a55"
}

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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