Pipeline run
de55fb90-ac75-4d22-a32d-49d8e9ff9d44
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
Captured for admin review
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Data Engineer
CASE Aslug: data-engineer · id: 2 · source: db
Exact alias hit on data-engineer (1.0) — no other alias at this confidence; skill_top data-engineer 0.17 does not contradict
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Job description We are looking for an ETL Developer to support our team with the data transformation process, implementing ETL development lifecycle, creating data warehousing and working with source data. The ideal candidate has worked in a large-scale data collection process and must be capable of taking on new challenges. The right individual will have the opportunity to work with a dedicated team in a growing environment. Utilizing an ETL (Extract, Transform, and Load) method, load a data warehouse with large amounts of raw data. Load time-series data into the data warehouse. Minimize the amount of data sent to the data warehouse. Ensure that the source system being extracted from remains in a consistent state. Debug problems in ETL programs. Design, code, test and manage various applications Collaborate with engineering team and product team to establish best products • Follow outlined standards of quality related to code and systems Bachelor's degree in Computer Science or relevant field - in progress is also accepted 3+ years of SQL development (MSSQL) 2+ years of ETL Experience Report writer SSIS Experience Stored procedures knowledge Correspondence Engine
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- SQL (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Query Language
- Vendor
- ANSI
- License
- unknown
- Year introduced
- 1974
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: SQL appears in a large share of data, backend, and analytics job descriptions and remains the default query language for PostgreSQL, MySQL, and cloud warehouses like Snowflake/BigQuery.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 97
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Pega Programming Languages & DSLs Catalog dimension db id 267
Library dimension (catalog)
Roles linked in library: Pega Developer
-
Programming Languages & 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 saved |
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)
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
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Databases
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- FAST
- Typical lifespan
- SHORT_LIVED
- Version strategy
- VERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- FAST
- Typical lifespan
- SHORT_LIVED
- Version strategy
- VERSIONED
All API 3 persistence rows
Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.
| Skill | Tag | Dimension | Skill↔dim | Role↔dim | Outcome | Notes |
|---|---|---|---|---|---|---|
| SQL | in_db |
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| SQL | in_db |
Programming Languages & 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 saved | |
| Microsoft SQL Server | 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 | Data Warehousing | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | SSIS | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Stored Procedures | type=Databases subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | Report Writer | type=Data Engineering Tools subtype=general nature=TOOL lifespan=SHORT_LIVED | |
| canonical_skill_proposed | Correspondence Engine | type=Data Engineering Tools subtype=general nature=TOOL lifespan=SHORT_LIVED | |
| dimension_skill_link_proposed | Microsoft SQL Server ↔ Relational Database Design |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "Other"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE - Computer Science (or relevant)",
"raw": "Bachelor\u0027s degree in Computer Science or relevant field - in progress is also accepted",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 3,
"raw": "3+ years of SQL development (MSSQL)"
},
"job_locations": [],
"role": "ETL Developer",
"role_aliases": [
"ETL Engineer",
"Data Engineer",
"Data Integration Developer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Role Overview",
"heading_was_present": false,
"source_marker": {
"first_5_words": "We are looking for an",
"last_5_words": "in a growing environment."
},
"text": "We are looking for an ETL Developer to support our team with the data transformation process, implementing ETL development lifecycle, creating data warehousing and working with source data. The ideal candidate has worked in a large-scale data collection process and must be capable of taking on new challenges. The right individual will have the opportunity to work with a dedicated team in a growing environment.",
"word_count": 56
},
{
"bullet_count": 7,
"heading": "Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Utilizing an ETL (Extract,",
"last_5_words": "related to code and systems."
},
"text": "Utilizing an ETL (Extract, Transform, and Load) method, load a data warehouse with large amounts of raw data.\nLoad time-series data into the data warehouse.\nMinimize the amount of data sent to the data warehouse.\nEnsure that the source system being extracted from remains in a consistent state.\nDebug problems in ETL programs.\nDesign, code, test and manage various applications.\nCollaborate with engineering team and product team to establish best products.\nFollow outlined standards of quality related to code and systems.",
"word_count": 83
},
{
"bullet_count": 7,
"heading": "Qualifications",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Bachelor\u0027s degree in Computer",
"last_5_words": "knowledge.\nCorrespondence Engine."
},
"text": "Bachelor\u0027s degree in Computer Science or relevant field - in progress is also accepted.\n3+ years of SQL development (MSSQL).\n2+ years of ETL Experience.\nReport writer.\nSSIS Experience.\nStored procedures knowledge.\nCorrespondence Engine.",
"word_count": 36
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "ETL"
},
{
"is_primary": true,
"skill_name": "Data Warehousing"
},
{
"is_primary": true,
"skill_name": "SQL"
},
{
"is_primary": true,
"skill_name": "Microsoft SQL Server"
},
{
"is_primary": true,
"skill_name": "SSIS"
},
{
"is_primary": true,
"skill_name": "Stored Procedures"
},
{
"is_primary": false,
"skill_name": "Report Writer"
},
{
"is_primary": false,
"skill_name": "Correspondence Engine"
}
],
"jd_role": {
"display_name": "ETL Developer",
"rationale": null,
"role_aliases": [
"ETL Engineer",
"Data Engineer",
"Data Integration Developer"
],
"role_archetype": "Data",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": null,
"domain": {
"primary": {
"aliases": [],
"domain": "Other"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE - Computer Science (or relevant)",
"raw": "Bachelor\u0027s degree in Computer Science or relevant field - in progress is also accepted",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 3,
"raw": "3+ years of SQL development (MSSQL)"
},
"job_locations": [],
"role": "ETL Developer",
"role_aliases": [
"ETL Engineer",
"Data Engineer",
"Data Integration Developer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Role Overview",
"heading_was_present": false,
"source_marker": {
"first_5_words": "We are looking for an",
"last_5_words": "in a growing environment."
},
"text": "We are looking for an ETL Developer to support our team with the data transformation process, implementing ETL development lifecycle, creating data warehousing and working with source data. The ideal candidate has worked in a large-scale data collection process and must be capable of taking on new challenges. The right individual will have the opportunity to work with a dedicated team in a growing environment.",
"word_count": 56
},
{
"bullet_count": 7,
"heading": "Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Utilizing an ETL (Extract,",
"last_5_words": "related to code and systems."
},
"text": "Utilizing an ETL (Extract, Transform, and Load) method, load a data warehouse with large amounts of raw data.\nLoad time-series data into the data warehouse.\nMinimize the amount of data sent to the data warehouse.\nEnsure that the source system being extracted from remains in a consistent state.\nDebug problems in ETL programs.\nDesign, code, test and manage various applications.\nCollaborate with engineering team and product team to establish best products.\nFollow outlined standards of quality related to code and systems.",
"word_count": 83
},
{
"bullet_count": 7,
"heading": "Qualifications",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Bachelor\u0027s degree in Computer",
"last_5_words": "knowledge.\nCorrespondence Engine."
},
"text": "Bachelor\u0027s degree in Computer Science or relevant field - in progress is also accepted.\n3+ years of SQL development (MSSQL).\n2+ years of ETL Experience.\nReport writer.\nSSIS Experience.\nStored procedures knowledge.\nCorrespondence Engine.",
"word_count": 36
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "de55fb90-ac75-4d22-a32d-49d8e9ff9d44",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 1.0,
"slug": "data-engineer",
"total_count": null
}
],
"kra_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": [
{
"kra_text": "Implements data transformation, cleansing, deduplication, and enrichment logic to convert raw source data into analytics-ready curated datasets.",
"sentence": "Utilizing an ETL (Extract, Transform, and Load) method, load a data warehouse with large amounts of raw data.",
"similarity": 0.5627
},
{
"kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "We are looking for an ETL Developer to support our team with the data transformation process, implementing ETL development lifecycle, creating data warehousing and working with source data.",
"similarity": 0.5418
},
{
"kra_text": "Optimizes pipeline throughput, partitioning strategies, and query performance across cloud data warehouses like Snowflake, BigQuery, or Redshift.",
"sentence": "Minimize the amount of data sent to the data warehouse.",
"similarity": 0.5285
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.5444,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "Flutter Developer",
"kra_matches": [
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Collaborate with engineering team and product team to establish best products.",
"similarity": 0.7055
},
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Design, code, test and manage various applications.",
"similarity": 0.5117
},
{
"kra_text": "optimize responsiveness and performance",
"sentence": "Follow outlined standards of quality related to code and systems.",
"similarity": 0.3748
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 74,
"score": 0.5307,
"slug": "flutter-developer",
"total_count": null
},
{
"display_name": "React Native Developer",
"kra_matches": [
{
"kra_text": "maintain code quality",
"sentence": "Follow outlined standards of quality related to code and systems.",
"similarity": 0.6251
},
{
"kra_text": "maintain code quality",
"sentence": "Design, code, test and manage various applications.",
"similarity": 0.4353
},
{
"kra_text": "support offline-aware data flow",
"sentence": "Minimize the amount of data sent to the data warehouse.",
"similarity": 0.4025
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 73,
"score": 0.4876,
"slug": "react-native-developer",
"total_count": null
},
{
"display_name": "DevOps Engineer",
"kra_matches": [
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "Collaborate with engineering team and product team to establish best products.",
"similarity": 0.5449
},
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "Design, code, test and manage various applications.",
"similarity": 0.5253
},
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "Follow outlined standards of quality related to code and systems.",
"similarity": 0.3902
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 10,
"score": 0.4868,
"slug": "devops-engineer",
"total_count": null
},
{
"display_name": "Angular Frontend Developer",
"kra_matches": [
{
"kra_text": "collaboration with design and QA",
"sentence": "Collaborate with engineering team and product team to establish best products.",
"similarity": 0.5304
},
{
"kra_text": "collaboration with design and QA",
"sentence": "Design, code, test and manage various applications.",
"similarity": 0.4707
},
{
"kra_text": "code review and refactoring",
"sentence": "Follow outlined standards of quality related to code and systems.",
"similarity": 0.442
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 90,
"score": 0.481,
"slug": "angular-frontend-developer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"SQL"
],
"role_id": 2,
"score": 0.1667,
"slug": "data-engineer",
"total_count": 6
},
{
"display_name": "Pega Developer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"SQL"
],
"role_id": 24,
"score": 0.1667,
"slug": "pega-developer",
"total_count": 6
},
{
"display_name": "Engineering Manager",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"SQL"
],
"role_id": 121,
"score": 0.1667,
"slug": "engineering-manager",
"total_count": 6
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "A",
"chosen_role": {
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 1.0,
"slug": "data-engineer",
"total_count": null
},
"confidence": 1.0,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [],
"matched_kras": [],
"matched_skills": [],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.17 does not contradict",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 511,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 23756,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "ETL",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 23758,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Warehousing",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 23760,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Microsoft SQL Server",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 23761,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "SSIS",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 23762,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Stored Procedures",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 23763,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Report Writer",
"status": "pending"
},
{
"is_primary": false,
"queue_id": 23764,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Correspondence Engine",
"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": 271,
"existing_alias_text": "SQL",
"input_term": "SQL",
"matched_canonical": {
"category_id": 6,
"display_name": "SQL",
"id": 101,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "sql",
"sub_category_id": 97,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "TODO: REMOVE AFTER TESTING \u2014 alias DB write disabled",
"alias_persisted": false,
"existing_alias_id": 135,
"existing_alias_text": "SQL Server",
"input_term": "Microsoft SQL Server",
"matched_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"
},
"matched_via": "embedding_alias"
}
],
"candidate_roles": [
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
},
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
},
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "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"
}
],
"chosen_role": {
"display_name": "Data Engineer",
"id": 2,
"rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.17 does not contradict",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Pega Programming Languages \u0026 DSLs",
"id": 267,
"rationale": "Programming languages and domain-specific languages used in Pega development.",
"slug": "pega-programming-languages-dsls",
"source": "db"
},
"input_skill": "SQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages \u0026 DSLs",
"id": 475,
"rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
"slug": "programming-languages-dsls",
"source": "db"
},
"input_skill": "SQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "SQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
},
{
"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": "Microsoft 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_final_skills": [
"ETL",
"Data Warehousing",
"SQL",
"Microsoft SQL Server",
"SSIS",
"Stored Procedures",
"Report Writer",
"Correspondence Engine"
],
"input_llm_skills": [
"ETL",
"Data Warehousing",
"SQL",
"Microsoft SQL Server",
"SSIS",
"Stored Procedures",
"Report Writer",
"Correspondence Engine"
],
"new_aliases_persisted": 0,
"run_id": "de55fb90-ac75-4d22-a32d-49d8e9ff9d44",
"skills_detail": [
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "ETL",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"skill_nature": "PRACTICE",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "etl",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Data Warehousing",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "data-warehousing",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "SQL",
"alias_type": "CANONICAL",
"id": 271,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 6,
"display_name": "SQL",
"id": 101,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "sql",
"sub_category_id": 97,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Pega Programming Languages \u0026 DSLs",
"id": 267,
"rationale": "Programming languages and domain-specific languages used in Pega development.",
"slug": "pega-programming-languages-dsls",
"source": "db"
},
"input_skill": "SQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages \u0026 DSLs",
"id": 475,
"rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
"slug": "programming-languages-dsls",
"source": "db"
},
"input_skill": "SQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "SQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_skill": "SQL",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"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": "Microsoft 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": "Microsoft SQL Server",
"matched_via": "embedding_alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "SSIS",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "ssis",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Stored Procedures",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Databases",
"skill_nature": "CONCEPT",
"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": "stored-procedures",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Report Writer",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "SHORT_LIVED",
"version_strategy": "VERSIONED",
"volatility": "FAST"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "report-writer",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Correspondence Engine",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "SHORT_LIVED",
"version_strategy": "VERSIONED",
"volatility": "FAST"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "correspondence-engine",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"ETL",
"Data Warehousing",
"SSIS",
"Stored Procedures",
"Report Writer",
"Correspondence Engine"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Data Engineer",
"id": 2,
"rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.17 does not contradict",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "ETL",
"tag": "new"
},
{
"skill": "Data Warehousing",
"tag": "new"
},
{
"skill": "SQL",
"tag": "in_db"
},
{
"skill": "Microsoft SQL Server",
"tag": "in_db"
},
{
"skill": "SSIS",
"tag": "new"
},
{
"skill": "Stored Procedures",
"tag": "new"
},
{
"skill": "Report Writer",
"tag": "new"
},
{
"skill": "Correspondence Engine",
"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": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Pega Programming Languages \u0026 DSLs",
"id": 267,
"rationale": "Programming languages and domain-specific languages used in Pega development.",
"slug": "pega-programming-languages-dsls",
"source": "db"
},
"dimension_id": 267,
"input_skill": "SQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 101,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages \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": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 21,
"input_skill": "SQL",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 101,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "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": "Microsoft SQL Server",
"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": "de55fb90-ac75-4d22-a32d-49d8e9ff9d44"
}