Pipeline run
400e2ca5-0258-4aaa-a701-1e3659d16079
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 0.11 does not contradict
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Job Role: Process Mining - Data Engineer (Back End data massaging) No of Position – 5 Work Location – Chennai, Noida, Bangalore, Pune, Hyderabad Experience - 2 years to 4 years Notice period – Immediate or 30 days only eligible Salary – Asper Market Standard Mandatory Skills: Relational Database, Related data structures, Schemas and RDBMS SQL queries Data Mining and Process Mining Responsibilities Keep up to date with technology and best practices of Business Intelligence and Process Mining implementations. Implement the UiPath Process Mining and solutions at our customers. Make sure the right things are implemented. Have procedures for validating this. Define, measure, and maintain sufficient implementation quality. Second line of support for software and solutions support. Detect opportunities and risks in projects. Make sure those are addressed. Actively provide feedback to Engineering and Product Management. Requirements: BE/B.Tech/MCA or other equivalent degree or other related fields (2+ years) of experience in Relational Database, and related data structures and schemas. Strong knowledge of Data structures and relational databases. Excellent skills with SQL queries, procedures, and functions. Passionate about evaluating complex data, with excellent analytical skills and knowledge about data warehouse schemas. Excited about Data Mining and Process Mining Excellent verbal and written communication skills Proactive and strong problem-solving skills Ability to document requirements and specifications Experience with Agile and Scrum development methodologies Ability to learn quickly and work independently or as part of a team Knowledge in any of the data visualization tools (MS PBI, tableau) would be an added advantage Exposure to O2C & P2P domain would be an added advantage
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
- 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
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- 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
- Relational Databases (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Domain
- Sub-category
- Relational Database Management
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Relational databases remain a hiring staple across most backend/data JDs, with PostgreSQL, MySQL, and SQL Server appearing routinely; cloud vendors also center managed RDBMS offerings, signaling broad adoption.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 37
- Sub-category id
- 1018
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
— | — |
Skipped — no persistable v3 meta for new skill
skill_not_in_db_v3_proposed
|
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 for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Databases
- Sub-category
- general
- Skill nature
- CONCEPT
- 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
- Agile (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Agile
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Agile appears in a large share of software job descriptions and is a standard hiring-pipeline requirement; Scrum/Kanban are commonly listed alongside it, showing broad market adoption.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 367
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Scrum (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Scrum
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Scrum appears in a large share of agile project-management and product-owner job descriptions, and Scrum Alliance/PSM certifications are widely requested in hiring pipelines.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 921
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Power BI (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Bi Analytics Platform
- Vendor
- Microsoft
- License
- proprietary
- Year introduced
- 2015
- Confidence
- 0.96
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Power BI appears frequently in BI/data analyst job descriptions and is a standard Microsoft analytics platform in enterprise stacks, with strong vendor support and broad adoption.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 111
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
BI and Visualization Tools Catalog dimension db id 31
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
BI and Visualization Tools
bi-and-visualization-tools
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Aliases — catalog
- Tableau (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Bi Analytics Platform
- Vendor
- Tableau Software
- License
- proprietary
- Year introduced
- 2003
- Confidence
- 0.96
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Tableau appears frequently in BI/data analyst job descriptions and remains a standard enterprise analytics platform with strong vendor support and broad adoption.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 111
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
BI and Visualization Tools Catalog dimension db id 31
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
BI and Visualization Tools
bi-and-visualization-tools
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
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 |
|---|---|---|---|---|---|---|
| Relational Database | new |
React Frontend Development
d_init_01
|
— | — | Skipped — no persistable v3 meta for new skill | skill_not_in_db_v3_proposed |
| SQL | in_db |
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| SQL | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Agile | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Scrum | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Power BI | in_db |
BI and Visualization Tools
bi-and-visualization-tools
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved | |
| Tableau | in_db |
BI and Visualization Tools
bi-and-visualization-tools
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | UiPath Process Mining | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Business Intelligence | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Process Mining | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Warehouse | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Mining | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| dimension_skill_link_proposed | Relational Database ↔ React Frontend Development |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": {
"currency": null,
"max": null,
"min": null,
"period": null,
"raw": "Asper Market Standard"
},
"domain": {
"primary": {
"aliases": [],
"domain": "Other"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE/MCA - Other Related Fields",
"raw": "BE/B.Tech/MCA or other equivalent degree or other related fields",
"requirement": "required"
}
],
"experience": {
"max": 4,
"min": 2,
"raw": "2 years to 4 years"
},
"job_locations": [
{
"aliases": [
"Madras"
],
"city": "Chennai",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [],
"city": "Noida",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [
"Bengaluru"
],
"city": "Bangalore",
"country": "India",
"state": "Karnataka",
"work_mode": null
},
{
"aliases": [],
"city": "Pune",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [],
"city": "Hyderabad",
"country": "India",
"state": null,
"work_mode": null
}
],
"role": "Process Mining - Data Engineer (Back End data massaging)",
"role_aliases": [
"Data Engineer",
"Process Mining Engineer",
"Backend Data Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 7,
"heading": "Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Keep up to date with",
"last_5_words": "Engineering and Product Management."
},
"text": "Keep up to date with technology and best practices of Business Intelligence and Process Mining implementations.\nImplement the UiPath Process Mining and solutions at our customers.\nMake sure the right things are implemented. Have procedures for validating this.\nDefine, measure, and maintain sufficient implementation quality.\nSecond line of support for software and solutions support.\nDetect opportunities and risks in projects. Make sure those are addressed.\nActively provide feedback to Engineering and Product Management.",
"word_count": 66
},
{
"bullet_count": 12,
"heading": "Requirements",
"heading_was_present": true,
"source_marker": {
"first_5_words": "(2+ years) of experience",
"last_5_words": "O2C \u0026 P2P domain would"
},
"text": "(2+ years) of experience in Relational Database, and related data structures and schemas.\nStrong knowledge of Data structures and relational databases.\nExcellent skills with SQL queries, procedures, and functions.\nPassionate about evaluating complex data, with excellent analytical skills and knowledge about data warehouse schemas.\nExcited about Data Mining and Process Mining\nExcellent verbal and written communication skills\nProactive and strong problem-solving skills\nAbility to document requirements and specifications\nExperience with Agile and Scrum development methodologies\nAbility to learn quickly and work independently or as part of a team\nKnowledge in any of the data visualization tools (MS PBI, tableau) would be an added advantage\nExposure to O2C \u0026 P2P domain would be an added advantage",
"word_count": 116
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "UiPath Process Mining"
},
{
"is_primary": true,
"skill_name": "Business Intelligence"
},
{
"is_primary": true,
"skill_name": "Process Mining"
},
{
"is_primary": true,
"skill_name": "Relational Database"
},
{
"is_primary": true,
"skill_name": "SQL"
},
{
"is_primary": true,
"skill_name": "Data Warehouse"
},
{
"is_primary": true,
"skill_name": "Data Mining"
},
{
"is_primary": true,
"skill_name": "Agile"
},
{
"is_primary": true,
"skill_name": "Scrum"
},
{
"is_primary": false,
"skill_name": "Power BI"
},
{
"is_primary": false,
"skill_name": "Tableau"
}
],
"jd_role": {
"display_name": "Process Mining - Data Engineer (Back End data massaging)",
"rationale": null,
"role_aliases": [
"Data Engineer",
"Process Mining Engineer",
"Backend Data Engineer"
],
"role_archetype": "Data",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"certifications": [],
"company_name": null,
"ctc": {
"currency": null,
"max": null,
"min": null,
"period": null,
"raw": "Asper Market Standard"
},
"domain": {
"primary": {
"aliases": [],
"domain": "Other"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE/MCA - Other Related Fields",
"raw": "BE/B.Tech/MCA or other equivalent degree or other related fields",
"requirement": "required"
}
],
"experience": {
"max": 4,
"min": 2,
"raw": "2 years to 4 years"
},
"job_locations": [
{
"aliases": [
"Madras"
],
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"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [],
"city": "Noida",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [
"Bengaluru"
],
"city": "Bangalore",
"country": "India",
"state": "Karnataka",
"work_mode": null
},
{
"aliases": [],
"city": "Pune",
"country": "India",
"state": null,
"work_mode": null
},
{
"aliases": [],
"city": "Hyderabad",
"country": "India",
"state": null,
"work_mode": null
}
],
"role": "Process Mining - Data Engineer (Back End data massaging)",
"role_aliases": [
"Data Engineer",
"Process Mining Engineer",
"Backend Data Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 7,
"heading": "Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Keep up to date with",
"last_5_words": "Engineering and Product Management."
},
"text": "Keep up to date with technology and best practices of Business Intelligence and Process Mining implementations.\nImplement the UiPath Process Mining and solutions at our customers.\nMake sure the right things are implemented. Have procedures for validating this.\nDefine, measure, and maintain sufficient implementation quality.\nSecond line of support for software and solutions support.\nDetect opportunities and risks in projects. Make sure those are addressed.\nActively provide feedback to Engineering and Product Management.",
"word_count": 66
},
{
"bullet_count": 12,
"heading": "Requirements",
"heading_was_present": true,
"source_marker": {
"first_5_words": "(2+ years) of experience",
"last_5_words": "O2C \u0026 P2P domain would"
},
"text": "(2+ years) of experience in Relational Database, and related data structures and schemas.\nStrong knowledge of Data structures and relational databases.\nExcellent skills with SQL queries, procedures, and functions.\nPassionate about evaluating complex data, with excellent analytical skills and knowledge about data warehouse schemas.\nExcited about Data Mining and Process Mining\nExcellent verbal and written communication skills\nProactive and strong problem-solving skills\nAbility to document requirements and specifications\nExperience with Agile and Scrum development methodologies\nAbility to learn quickly and work independently or as part of a team\nKnowledge in any of the data visualization tools (MS PBI, tableau) would be an added advantage\nExposure to O2C \u0026 P2P domain would be an added advantage",
"word_count": 116
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "400e2ca5-0258-4aaa-a701-1e3659d16079",
"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": "Designs dimensional models, star schemas, data vault structures, and curated data mart tables to support BI tools and self-service analytics consumption.",
"sentence": "Passionate about evaluating complex data, with excellent analytical skills and knowledge about data warehouse schemas.",
"similarity": 0.5902
},
{
"kra_text": "Designs dimensional models, star schemas, data vault structures, and curated data mart tables to support BI tools and self-service analytics consumption.",
"sentence": "(2+ years) of experience in Relational Database, and related data structures and schemas.",
"similarity": 0.4885
},
{
"kra_text": "Designs dimensional models, star schemas, data vault structures, and curated data mart tables to support BI tools and self-service analytics consumption.",
"sentence": "Knowledge in any of the data visualization tools (MS PBI, tableau) would be an added advantage",
"similarity": 0.4568
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.5118,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "Fullstack Developer",
"kra_matches": [
{
"kra_text": "Works closely with product managers and UX designers to translate requirements and wireframes into working software features through iterative development.",
"sentence": "Actively provide feedback to Engineering and Product Management.",
"similarity": 0.5486
},
{
"kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
"sentence": "(2+ years) of experience in Relational Database, and related data structures and schemas.",
"similarity": 0.505
},
{
"kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
"sentence": "Excellent skills with SQL queries, procedures, and functions.",
"similarity": 0.4678
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 15,
"score": 0.5071,
"slug": "full-stack-engineer",
"total_count": null
},
{
"display_name": "Flutter Developer",
"kra_matches": [
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Actively provide feedback to Engineering and Product Management.",
"similarity": 0.5265
},
{
"kra_text": "translate product and design requirements",
"sentence": "Ability to document requirements and specifications",
"similarity": 0.5035
},
{
"kra_text": "support release readiness",
"sentence": "Second line of support for software and solutions support.",
"similarity": 0.458
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 74,
"score": 0.496,
"slug": "flutter-developer",
"total_count": null
},
{
"display_name": "Cyber Security Engineer",
"kra_matches": [
{
"kra_text": "Performs threat modeling, security architecture reviews, and quantitative risk analysis for new product features and infrastructure changes.",
"sentence": "Detect opportunities and risks in projects.",
"similarity": 0.5415
},
{
"kra_text": "Defines secure engineering standards, secure coding guidelines, threat intelligence feeds, and compliance requirements for the organization.",
"sentence": "Define, measure, and maintain sufficient implementation quality.",
"similarity": 0.4373
},
{
"kra_text": "Performs threat modeling, security architecture reviews, and quantitative risk analysis for new product features and infrastructure changes.",
"sentence": "Actively provide feedback to Engineering and Product Management.",
"similarity": 0.4356
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 5,
"score": 0.4715,
"slug": "cybersecurity-engineer",
"total_count": null
},
{
"display_name": "React Native Developer",
"kra_matches": [
{
"kra_text": "maintain code quality",
"sentence": "Define, measure, and maintain sufficient implementation quality.",
"similarity": 0.5703
},
{
"kra_text": "maintain code quality",
"sentence": "Make sure the right things are implemented.",
"similarity": 0.4333
},
{
"kra_text": "maintain code quality",
"sentence": "Actively provide feedback to Engineering and Product Management.",
"similarity": 0.3481
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 73,
"score": 0.4506,
"slug": "react-native-developer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"SQL"
],
"role_id": 2,
"score": 0.1111,
"slug": "data-engineer",
"total_count": 9
},
{
"display_name": "Pega Developer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"SQL"
],
"role_id": 24,
"score": 0.1111,
"slug": "pega-developer",
"total_count": 9
}
]
},
"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 0.11 does not contradict",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 80,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 5173,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "UiPath Process Mining",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 5174,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Business Intelligence",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 5175,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Process Mining",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 5176,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Relational Database",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 5177,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Warehouse",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 5178,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Mining",
"status": "pending"
}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
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"alias_persisted": false,
"existing_alias_id": 1988,
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"input_term": "Relational Database",
"matched_canonical": {
"category_id": 37,
"display_name": "Relational Databases",
"id": 1345,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "relational-databases",
"sub_category_id": 1018,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "embedding_alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 271,
"existing_alias_text": "SQL",
"input_term": "SQL",
"matched_canonical": {
"category_id": 6,
"display_name": "SQL",
"id": 101,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "sql",
"sub_category_id": 97,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 868,
"existing_alias_text": "Agile",
"input_term": "Agile",
"matched_canonical": {
"category_id": 8,
"display_name": "Agile",
"id": 520,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
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"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": 1851,
"existing_alias_text": "Scrum",
"input_term": "Scrum",
"matched_canonical": {
"category_id": 8,
"display_name": "Scrum",
"id": 1215,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "scrum",
"sub_category_id": 921,
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},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 360,
"existing_alias_text": "Power BI",
"input_term": "Power BI",
"matched_canonical": {
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"display_name": "Power BI",
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"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "power-bi",
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},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 359,
"existing_alias_text": "Tableau",
"input_term": "Tableau",
"matched_canonical": {
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"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
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"typical_lifespan": "EVERGREEN",
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},
"matched_via": "alias"
}
],
"candidate_roles": [
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},
{
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"slug": "data-engineer",
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}
],
"chosen_role": {
"display_name": "Data Engineer",
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"rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.11 does not contradict",
"role_archetype": null,
"slug": "data-engineer",
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},
"dimensions": [
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"dimension": {
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"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
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},
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"roles_from_db": []
},
{
"dimension": {
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"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",
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},
"input_skill": "SQL",
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"roles_from_db": [
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"display_name": "Pega Developer",
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"slug": "pega-developer",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
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"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "SQL",
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"roles_from_db": [
{
"display_name": "Data Engineer",
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}
]
},
{
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},
"input_skill": "Agile",
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"roles_from_db": []
},
{
"dimension": {
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"display_name": "React Frontend Development",
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},
"input_skill": "Scrum",
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"roles_from_db": []
},
{
"dimension": {
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},
"input_skill": "Power BI",
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"roles_from_db": [
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}
]
},
{
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"source": "db"
},
"input_skill": "Tableau",
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{
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"role_archetype": null,
"slug": "data-engineer",
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}
]
}
],
"input_final_skills": [
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"Business Intelligence",
"Process Mining",
"Relational Database",
"SQL",
"Data Warehouse",
"Data Mining",
"Agile",
"Scrum",
"Power BI",
"Tableau"
],
"input_llm_skills": [
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"Business Intelligence",
"Process Mining",
"Relational Database",
"SQL",
"Data Warehouse",
"Data Mining",
"Agile",
"Scrum",
"Power BI",
"Tableau"
],
"new_aliases_persisted": 0,
"run_id": "400e2ca5-0258-4aaa-a701-1e3659d16079",
"skills_detail": [
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "UiPath Process Mining",
"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,
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"skill_id": "uipath-process-mining",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Business Intelligence",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
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},
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},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
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"input_skill": "Process Mining",
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"new_skill_meta": {
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},
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"placed": null,
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"skill_id": "process-mining",
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},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
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"id": 1988,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
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},
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{
"dimension": {
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"source": "db"
},
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"roles_from_db": []
}
],
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"matched_via": "embedding_alias",
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"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
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}
],
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},
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{
"dimension": {
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},
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]
},
{
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]
}
],
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"source_tag": "db",
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},
{
"aliases_in_db": [],
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},
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},
"source_tag": "llm",
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},
{
"aliases_in_db": [],
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},
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},
{
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],
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},
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},
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}
],
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},
{
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}
],
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}
],
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{
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]
}
],
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},
{
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],
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"source": "db"
},
"input_skill": "Tableau",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_skill": "Tableau",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"UiPath Process Mining",
"Business Intelligence",
"Process Mining",
"Data Warehouse",
"Data Mining"
]
}
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 0.11 does not contradict",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "UiPath Process Mining",
"tag": "new"
},
{
"skill": "Business Intelligence",
"tag": "new"
},
{
"skill": "Process Mining",
"tag": "new"
},
{
"skill": "Relational Database",
"tag": "in_db"
},
{
"skill": "SQL",
"tag": "in_db"
},
{
"skill": "Data Warehouse",
"tag": "new"
},
{
"skill": "Data Mining",
"tag": "new"
},
{
"skill": "Agile",
"tag": "in_db"
},
{
"skill": "Scrum",
"tag": "in_db"
},
{
"skill": "Power BI",
"tag": "in_db"
},
{
"skill": "Tableau",
"tag": "in_db"
}
],
"llm_cost_api1_usd": null,
"llm_cost_api2_usd": null,
"llm_cost_api3_usd": null,
"llm_cost_total_usd": null,
"persistence": {
"items": [
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 96,
"input_skill": "Relational Database",
"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": [],
"skill_dimension_saved": false,
"skill_id": null,
"skill_tag": "new",
"skipped_reason": "skill_not_in_db_v3_proposed"
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Pega Programming Languages \u0026 DSLs",
"id": 267,
"rationale": "Programming languages and domain-specific languages used in Pega development.",
"slug": "pega-programming-languages-dsls",
"source": "db"
},
"dimension_id": 267,
"input_skill": "SQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 101,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"dimension_id": 21,
"input_skill": "SQL",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 101,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 96,
"input_skill": "Agile",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 520,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 96,
"input_skill": "Scrum",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 1215,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "BI and Visualization Tools",
"id": 31,
"rationale": "Tools used to expose curated data to analysts and business users through dashboards, reports, and semantic exploration. Data engineers support these tools by shaping reliable datasets and performant models.",
"slug": "bi-and-visualization-tools",
"source": "db"
},
"dimension_id": 31,
"input_skill": "Power BI",
"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": 151,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "BI and Visualization Tools",
"id": 31,
"rationale": "Tools used to expose curated data to analysts and business users through dashboards, reports, and semantic exploration. Data engineers support these tools by shaping reliable datasets and performant models.",
"slug": "bi-and-visualization-tools",
"source": "db"
},
"dimension_id": 31,
"input_skill": "Tableau",
"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": 150,
"skill_tag": "in_db",
"skipped_reason": null
}
],
"new_skills_created": 0,
"role_dimension_saved": 0,
"skill_dimension_saved": 0,
"skipped": 1
},
"planner_output": null,
"run_id": "400e2ca5-0258-4aaa-a701-1e3659d16079"
}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.