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Pipeline run

e42f5807-aca0-4270-8c34-7ceffa95b25d

Pipeline LLM cost (USD)
API 1: $0.0065 API 2: $0.0002 API 3: $0.0000 Total: $0.0067

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
SPARSE JD sources · ai_index: jd · nature_of_work: no_kras · tech_stack_maturity: jd
Nature of work no kras
Vague JD — no KRAs present to derive a specific nature of work.
Tech stack maturity
Mainstream Legacy
Hive and SQL Server are mature, widely adopted data-stack technologies, and the role centers on conventional ETL/ELT patterns rather than cloud-native or bleeding-edge tooling.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
0.20 / 5
· Title match
Has AI skill
· AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1): Cursor
Frameworks (×2):
Models / concepts (×3):
Evidence — skills matched in JD (7)
SSIS Talend Python Hive SQL Server T-SQL PySpark
Skill cluster (2 dimension groups, role-scoped)
Python Programming
Python
Cross-cutting / unaligned
SSIS Talend Hive SQL Server T-SQL PySpark

Signals

Skill python-backend-developer
0.33
Alias
KRA data-engineer
0.47

Post-classification

Centroidupdated · n=15
Alias collision log
New-role queue
New skills captured4
New KRA captured

Captured for admin review

SSIS primary ETL / ELT Developer pending
Talend primary ETL / ELT Developer pending
T-SQL primary ETL / ELT Developer pending
PySpark ETL / ELT Developer pending
Status: completed Created: 2026-05-27T16:38:58.896914Z Updated: 2026-05-27T16:40:05.824392Z API 3 duration: 20062 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 ETL tools and SQL-heavy transformation work, especially SSIS, Talend, Python, and SQL Server, which best matches ETL/ELT development.

Matched skills

SSISTalendPythonHiveSQL ServerT-SQLviewsprocedurescursorscomplex joinsuser defined functionstriggersPySpark

Matched dimensions

ETL/ELT DevelopmentSQL Query DevelopmentData IntegrationBig Data Processing

Matched KRAs

Have exhaustive experience in SSIS, Talend, Python, Hive and SQL ServerExpert in writing T-SQL queries, views, procedures, cursorsImplemented complex queryGood to have PySpark knowledgeExperience with Python+ Talend

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

• Have exhaustive experience in SSIS, Talend, Python, Hive and SQL Server. 
• Expert in writing T-SQL queries, views, procedures, cursors, Complex joins, user defined functions and triggers, implemented complex query.
• Good to have PySpark knowledge
• Experience with Python+ Talend

Skills from this JD

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

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

Aliases — catalog

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

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

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

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer

  • Programming Languages Catalog dimension db id 1

    Library dimension (catalog)

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

  • Programming Languages & DSLs Catalog dimension db id 475

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

  • Programming Languages and Scripting Catalog dimension db id 59

    Library dimension (catalog)

    Roles linked in library: Cyber Security Engineer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

  • Programming Languages for ML Systems Catalog dimension db id 39

    Library dimension (catalog)

    Roles linked in library: ML Engineer, MLOps Engineer

  • Programming Languages for XR Catalog dimension db id 97

    Library dimension (catalog)

    Roles linked in library: AR/VR Engineer

  • Python Programming Catalog dimension db id 290

    Library dimension (catalog)

    Roles linked in library: Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Hive Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Hive id=2754 · hive

Aliases — catalog

  • Hive (CANONICAL) primary

Context tags (catalog)

Apache Apache Hive Bucketing ETL HQL Hive Metastore Hive SerDe HiveQL MapReduce SQL SQL-on-Hadoop big data bucketing columnar storage data lakes data warehousing integration metadata partitioning schema evolution

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Local Key Value Store
Vendor
Apache Software Foundation
License
apache_2
Year introduced
2010
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Hive appears in Flutter/mobile JDs and package docs, but JD volume is far below SQLite/Realm and it’s mainly used for local key-value storage in Flutter apps.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
3
Sub-category id
2242
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Local Persistence and Offline Behavior Catalog dimension db id 85

    Library dimension (catalog)

    Roles linked in library: Android Developer, Flutter Developer, Hybrid Mobile Developer, Native Mobile Developer, React Native Developer, iOS Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Local Persistence and Offline Behavior
local-persistence-and-offline-behavior
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL Server Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: SQL Server id=18 · sql-server

Aliases — catalog

  • SQL Server (CANONICAL) primary
  • SQL Server 2000 (VERSION)
  • SQL Server 2005 (VERSION)
  • SQL Server 2008 (VERSION)
  • SQL Server 2012 (VERSION)
  • SQL Server 2014 (VERSION)
  • SQL Server 2016 (VERSION)
  • SQL Server 2017 (VERSION)
  • SQL Server 2019 (VERSION)
  • SQL Server 2022 (VERSION)
  • SQL Server 6.5 (VERSION)
  • SQL Server 7.0 (VERSION)

Context tags (catalog)

Always On CLR Integration Clustered Index ETL Execution Plan Linked Servers Query Store Replication SQL Agent SQL Server Agent SQL Server Integration Services SQL Server Management Studio SQL Server Reporting Services SSIS SSMS SSRS Stored Procedures T-SQL TempDB backup and recovery backup and restore clustering data migration data warehousing database design database normalization indexing performance tuning query optimization replication stored procedures transaction log transaction logs

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Relational Database
Vendor
Microsoft
License
proprietary
Year introduced
1989
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: SQL Server appears in many enterprise job descriptions and remains a major Microsoft-supported RDBMS with active Azure SQL/SQL Server demand; it is a common hiring-pipeline staple, not a sunset technology.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
3
Sub-category id
29
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Relational 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
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
T-SQL 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
Programming Languages
Sub-category
general
Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
PySpark Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Apache Spark id=1350 · apache-spark

Aliases — catalog

  • Apache Spark (CANONICAL)
  • apache spark 3 (VERSION)
  • spark (VERSION)
  • spark 3 (VERSION)
  • spark 3.x (VERSION)
  • spark3 (VERSION)

Context tags (catalog)

Apache Kafka Cluster Manager DAGScheduler Data Lake DataFrame ETL Hadoop MLlib Machine Learning PySpark RDD Scala Spark SQL Spark Streaming SparkSession

Stored enrichment (catalog DB)

Category
Framework
Sub-category
Distributed Data Processing Framework
Vendor
Apache Software Foundation
License
apache_2
Year introduced
2010
Confidence
0.94
Version strategy
SEPARATE_ENTITY
Version tag
3.x

Maturity reasoning: Apache Spark appears in many data engineering JDs and remains a standard for distributed ETL/ELT; its GitHub and vendor ecosystem activity stay strong, with Databricks and cloud platforms still promoting it.

Skill profile (library / DB)

Skill nature
FRAMEWORK
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
5
Sub-category id
1021
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
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed

All API 3 persistence rows

Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.

Skill Tag Dimension Skill↔dim Role↔dim Outcome Notes
Python in_db
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages
programming-languages
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages & DSLs
programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages and Scripting
programming-languages-and-scripting
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for ML Systems
programming-languages-for-ml-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Programming Languages for XR
programming-languages-for-xr
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Python in_db
Python Programming
python-programming
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Hive in_db
Local Persistence and Offline Behavior
local-persistence-and-offline-behavior
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL Server in_db
Relational Database Design
relational-database-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
PySpark new
ETL and ELT Tooling
etl-and-elt-tooling
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 SSIS | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Talend | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed T-SQL | type=Programming Languages subtype=general nature=LANGUAGE lifespan=EVERGREEN
dimension_skill_link_proposed PySpark ↔ ETL and ELT Tooling
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": [
    "Python",
    "Joins",
    "SQL Server",
    "Hive",
    "SQL",
    "Views"
  ],
  "role_archetype": "Engineering"
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "SSIS"
    },
    {
      "is_primary": true,
      "skill_name": "Talend"
    },
    {
      "is_primary": true,
      "skill_name": "Python"
    },
    {
      "is_primary": true,
      "skill_name": "Hive"
    },
    {
      "is_primary": true,
      "skill_name": "SQL Server"
    },
    {
      "is_primary": true,
      "skill_name": "T-SQL"
    },
    {
      "is_primary": false,
      "skill_name": "PySpark"
    }
  ],
  "jd_role": null,
  "nano_parsed": {
    "JD_type": "fail",
    "archetype_override_applied": true,
    "archetype_override_matched_skills": [
      "Python",
      "Joins",
      "SQL Server",
      "Hive",
      "SQL",
      "Views"
    ],
    "role_archetype": "Engineering"
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "e42f5807-aca0-4270-8c34-7ceffa95b25d",
  "stage3_signals": {
    "alias_found": false,
    "alias_match_roles": [],
    "kra_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": [
          {
            "kra_text": "Develops batch and real-time streaming data pipelines using Apache Spark, Apache Kafka, Apache Flink, or Airflow for data movement and processing at scale.",
            "sentence": "Have exhaustive experience in SSIS, Talend, Python, Hive and SQL Server.",
            "similarity": 0.4652
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 2,
        "score": 0.4652,
        "slug": "data-engineer",
        "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": "Have exhaustive experience in SSIS, Talend, Python, Hive and SQL Server.",
            "similarity": 0.3992
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 15,
        "score": 0.3992,
        "slug": "full-stack-engineer",
        "total_count": null
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": [
          {
            "kra_text": "Prepares, cleans, and transforms training datasets, manages feature stores, and builds feature engineering pipelines for model training.",
            "sentence": "Have exhaustive experience in SSIS, Talend, Python, Hive and SQL Server.",
            "similarity": 0.3919
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 3,
        "score": 0.3919,
        "slug": "ml-engineer",
        "total_count": null
      },
      {
        "display_name": "Backend Developer",
        "kra_matches": [
          {
            "kra_text": "Writes database access logic including SQL queries, ORM mappings, stored procedures, and migration scripts for relational databases like PostgreSQL and MySQL.",
            "sentence": "Have exhaustive experience in SSIS, Talend, Python, Hive and SQL Server.",
            "similarity": 0.3695
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 1,
        "score": 0.3695,
        "slug": "backend-engineer",
        "total_count": null
      },
      {
        "display_name": "AI Engineer",
        "kra_matches": [
          {
            "kra_text": "Designs and implements prompt engineering workflows, few-shot examples, chain-of-thought patterns, and structured output parsing for AI feature pipelines.",
            "sentence": "Have exhaustive experience in SSIS, Talend, Python, Hive and SQL Server.",
            "similarity": 0.351
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 13,
        "score": 0.351,
        "slug": "ai-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "Python Backend Developer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "Python",
          "SQL Server"
        ],
        "role_id": 80,
        "score": 0.3333,
        "slug": "python-backend-developer",
        "total_count": 6
      },
      {
        "display_name": "Backend Developer",
        "kra_matches": null,
        "matched_count": 2,
        "matched_skills": [
          "Python",
          "SQL Server"
        ],
        "role_id": 1,
        "score": 0.3333,
        "slug": "backend-engineer",
        "total_count": 6
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Python"
        ],
        "role_id": 3,
        "score": 0.1667,
        "slug": "ml-engineer",
        "total_count": 6
      },
      {
        "display_name": "Cyber Security Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Python"
        ],
        "role_id": 5,
        "score": 0.1667,
        "slug": "cybersecurity-engineer",
        "total_count": 6
      },
      {
        "display_name": "Android Developer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Hive"
        ],
        "role_id": 4,
        "score": 0.1667,
        "slug": "android-engineer",
        "total_count": 6
      }
    ]
  },
  "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/ELT Development",
      "SQL Query Development",
      "Data Integration",
      "Big Data Processing"
    ],
    "matched_kras": [
      "Have exhaustive experience in SSIS, Talend, Python, Hive and SQL Server",
      "Expert in writing T-SQL queries, views, procedures, cursors",
      "Implemented complex query",
      "Good to have PySpark knowledge",
      "Experience with Python+ Talend"
    ],
    "matched_skills": [
      "SSIS",
      "Talend",
      "Python",
      "Hive",
      "SQL Server",
      "T-SQL",
      "views",
      "procedures",
      "cursors",
      "complex joins",
      "user defined functions",
      "triggers",
      "PySpark"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=Data Engineering \u0026 Analytics; The JD is centered on ETL tools and SQL-heavy transformation work, especially SSIS, Talend, Python, and SQL Server, which best matches ETL/ELT development.",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 15,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 21206,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "SSIS",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 21207,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "Talend",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 21208,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "T-SQL",
        "status": "pending"
      },
      {
        "is_primary": false,
        "queue_id": 21209,
        "role_display_name": "ETL / ELT Developer",
        "role_slug": "etl-elt-developer",
        "skill_name": "PySpark",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
API 2 — extract-details
{
  "alias_matches": [
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 67,
      "existing_alias_text": "Python",
      "input_term": "Python",
      "matched_canonical": {
        "category_id": 6,
        "display_name": "Python",
        "id": 5,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "python",
        "sub_category_id": 96,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 4198,
      "existing_alias_text": "Hive",
      "input_term": "Hive",
      "matched_canonical": {
        "category_id": 3,
        "display_name": "Hive",
        "id": 2754,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "hive",
        "sub_category_id": 2242,
        "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": 135,
      "existing_alias_text": "SQL Server",
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        "category_id": 3,
        "display_name": "SQL Server",
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
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        "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": 2004,
      "existing_alias_text": "Apache Spark",
      "input_term": "PySpark",
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      "matched_via": "embedding_alias"
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      "slug": "ar-vr-engineer",
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      },
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      ]
    },
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      ]
    },
    {
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        "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
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        "source": "db"
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      "input_skill": "Python",
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      ]
    },
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        "slug": "programming-languages-for-data-work",
        "source": "db"
      },
      "input_skill": "Python",
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    },
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        "slug": "programming-languages-for-ml-systems",
        "source": "db"
      },
      "input_skill": "Python",
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      ]
    },
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        "source": "db"
      },
      "input_skill": "Python",
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      ]
    },
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        "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
        "slug": "python-programming",
        "source": "db"
      },
      "input_skill": "Python",
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      "roles_from_db": [
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      ]
    },
    {
      "dimension": {
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        "rationale": "On-device storage used for caching, offline support, and durable client state. This cluster is coherent because iOS apps often need to preserve user progress and data when connectivity is limited.",
        "slug": "local-persistence-and-offline-behavior",
        "source": "db"
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      "roles_from_db": [
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          "rationale": null,
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        },
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          "role_archetype": "Engineering",
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          "slug": "hybrid-mobile-developer",
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          "display_name": "Native Mobile Developer",
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        },
        {
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          "role_archetype": "Engineering",
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        },
        {
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          "rationale": null,
          "role_archetype": null,
          "slug": "ios-engineer",
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      ]
    },
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      ]
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        "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
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      "input_skill": "PySpark",
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      "new_skill_meta": {
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        {
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          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Python 2.x",
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          "id": 74,
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          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Python 3",
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        {
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          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Python 3.11",
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          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Python 3.12",
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          "id": 78,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "Python 3.x",
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          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "py",
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        {
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          "match_strategy": "CASE_INSENSITIVE"
        },
        {
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          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
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          "match_strategy": "CASE_INSENSITIVE"
        },
        {
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          "match_strategy": "CASE_INSENSITIVE"
        },
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          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
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        {
          "alias_text": "python3",
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          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "python3.x",
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          "match_strategy": "CASE_INSENSITIVE"
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      ],
      "canonical": {
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        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
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        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
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      "dimensions": [
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            "id": 248,
            "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
            "slug": "cloud-security-scripting-dsl-languages",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cloud Security Engineer",
              "id": 23,
              "rationale": null,
              "role_archetype": null,
              "slug": "cloud-security-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages",
            "id": 1,
            "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
            "slug": "programming-languages",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Backend Developer",
              "id": 1,
              "rationale": null,
              "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
              "slug": "backend-engineer",
              "source": "db"
            },
            {
              "display_name": "Fullstack Developer",
              "id": 15,
              "rationale": null,
              "role_archetype": null,
              "slug": "full-stack-engineer",
              "source": "db"
            },
            {
              "display_name": "Fullstack Developer",
              "id": 435,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "fullstack-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": "Python",
          "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 and Scripting",
            "id": 59,
            "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
            "slug": "programming-languages-and-scripting",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Cyber Security Engineer",
              "id": 5,
              "rationale": null,
              "role_archetype": null,
              "slug": "cybersecurity-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "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": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages for ML Systems",
            "id": 39,
            "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
            "slug": "programming-languages-for-ml-systems",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages for XR",
            "id": 97,
            "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
            "slug": "programming-languages-for-xr",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "AR/VR Engineer",
              "id": 8,
              "rationale": null,
              "role_archetype": null,
              "slug": "ar-vr-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Python Programming",
            "id": 290,
            "rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
            "slug": "python-programming",
            "source": "db"
          },
          "input_skill": "Python",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Python Backend Developer",
              "id": 80,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "python-backend-developer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Python",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Hive",
          "alias_type": "CANONICAL",
          "id": 4198,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 3,
        "display_name": "Hive",
        "id": 2754,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "hive",
        "sub_category_id": 2242,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Local Persistence and Offline Behavior",
            "id": 85,
            "rationale": "On-device storage used for caching, offline support, and durable client state. This cluster is coherent because iOS apps often need to preserve user progress and data when connectivity is limited.",
            "slug": "local-persistence-and-offline-behavior",
            "source": "db"
          },
          "input_skill": "Hive",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Android Developer",
              "id": 4,
              "rationale": null,
              "role_archetype": null,
              "slug": "android-engineer",
              "source": "db"
            },
            {
              "display_name": "Flutter Developer",
              "id": 74,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "flutter-developer",
              "source": "db"
            },
            {
              "display_name": "Hybrid Mobile Developer",
              "id": 11,
              "rationale": null,
              "role_archetype": null,
              "slug": "hybrid-mobile-developer",
              "source": "db"
            },
            {
              "display_name": "Native Mobile Developer",
              "id": 75,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "native-mobile-developer",
              "source": "db"
            },
            {
              "display_name": "React Native Developer",
              "id": 73,
              "rationale": null,
              "role_archetype": "Engineering",
              "slug": "react-native-developer",
              "source": "db"
            },
            {
              "display_name": "iOS Developer",
              "id": 6,
              "rationale": null,
              "role_archetype": null,
              "slug": "ios-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Hive",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "SQL Server",
          "alias_type": "CANONICAL",
          "id": 135,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "SQL Server 2000",
          "alias_type": "VERSION",
          "id": 138,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "SQL Server 2005",
          "alias_type": "VERSION",
          "id": 139,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "SQL Server 2008",
          "alias_type": "VERSION",
          "id": 140,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "SQL Server 2012",
          "alias_type": "VERSION",
          "id": 141,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "SQL Server 2014",
          "alias_type": "VERSION",
          "id": 142,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "SQL Server 2016",
          "alias_type": "VERSION",
          "id": 143,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "SQL Server 2017",
          "alias_type": "VERSION",
          "id": 144,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "SQL Server 2019",
          "alias_type": "VERSION",
          "id": 145,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "SQL Server 2022",
          "alias_type": "VERSION",
          "id": 146,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "SQL Server 6.5",
          "alias_type": "VERSION",
          "id": 136,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "SQL Server 7.0",
          "alias_type": "VERSION",
          "id": 137,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 3,
        "display_name": "SQL Server",
        "id": 18,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "TOOL",
        "slug": "sql-server",
        "sub_category_id": 29,
        "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": "SQL Server",
          "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": "SQL Server",
      "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": "T-SQL",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Programming Languages",
          "skill_nature": "LANGUAGE",
          "sub_category": "general",
          "typical_lifespan": "EVERGREEN",
          "version_strategy": "UNVERSIONED",
          "volatility": "STABLE"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "t-sql",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Apache Spark",
          "alias_type": "CANONICAL",
          "id": 2004,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "apache spark 3",
          "alias_type": "VERSION",
          "id": 2006,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "spark",
          "alias_type": "VERSION",
          "id": 2510,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "spark 3",
          "alias_type": "VERSION",
          "id": 2007,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "spark 3.x",
          "alias_type": "VERSION",
          "id": 2009,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "spark3",
          "alias_type": "VERSION",
          "id": 2008,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 5,
        "display_name": "Apache Spark",
        "id": 1350,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "FRAMEWORK",
        "slug": "apache-spark",
        "sub_category_id": 1021,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "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"
          },
          "input_skill": "PySpark",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Data Engineer",
              "id": 2,
              "rationale": null,
              "role_archetype": null,
              "slug": "data-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "PySpark",
      "matched_via": "embedding_alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "SSIS",
    "Talend",
    "T-SQL"
  ]
}
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 ETL tools and SQL-heavy transformation work, especially SSIS, Talend, Python, and SQL Server, which best matches ETL/ELT development.",
    "role_archetype": "Data",
    "slug": "etl-elt-developer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "SSIS",
      "tag": "new"
    },
    {
      "skill": "Talend",
      "tag": "new"
    },
    {
      "skill": "Python",
      "tag": "in_db"
    },
    {
      "skill": "Hive",
      "tag": "in_db"
    },
    {
      "skill": "SQL Server",
      "tag": "in_db"
    },
    {
      "skill": "T-SQL",
      "tag": "new"
    },
    {
      "skill": "PySpark",
      "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": "Cloud Security Scripting \u0026 DSL Languages",
          "id": 248,
          "rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
          "slug": "cloud-security-scripting-dsl-languages",
          "source": "db"
        },
        "dimension_id": 248,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cloud Security Engineer",
            "id": 23,
            "rationale": null,
            "role_archetype": null,
            "slug": "cloud-security-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 50,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages",
          "id": 1,
          "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
          "slug": "programming-languages",
          "source": "db"
        },
        "dimension_id": 1,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
            "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
            "slug": "backend-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 15,
            "rationale": null,
            "role_archetype": null,
            "slug": "full-stack-engineer",
            "source": "db"
          },
          {
            "display_name": "Fullstack Developer",
            "id": 435,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "fullstack-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "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": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 5,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 50,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages and Scripting",
          "id": 59,
          "rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
          "slug": "programming-languages-and-scripting",
          "source": "db"
        },
        "dimension_id": 59,
        "input_skill": "Python",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Cyber Security Engineer",
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