Pipeline run
536e62f4-6cbe-490e-a83c-c17c835fe278
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
a Design, develop, test, deploy and document a projects data quality procedures and its outputs b Document at a functional level how the procedures work within the data quality applications c The prim…
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Backend Developer
CASE Aslug: backend-engineer · id: 1 · source: db
Exact alias hit on backend-engineer (1.0) — no other alias at this confidence; skill_top data-engineer 0.12 does not contradict
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
About Accenture: Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services-all powered by the world's largest network of Advanced Technology and Intelligent Operations centers. Our 674,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries.We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. Visit us at www.accenture.com Accenture | Let there be change We embrace change to create 360-degree value www.accenture.com Project Role :Application Developer Project Role Description :Design, build and configure applications to meet business process and application requirements. Management Level :10 Work Experience :4-6 years Work location :Pune Must Have Skills : Good To Have Skills : Job Requirements : Key Responsibilities : a Design, develop, test, deploy and document a projects data quality procedures and its outputs b Document at a functional level how the procedures work within the data quality applications c The primary tasks associated with this role are to use IDQ to profile the project source data, define or confirm the definition of the metadata, cleanse and accurately check the project data, check for duplicate or redundant records, and provide information on how to proceed with backend ETL processes Technical Experience : a knowledge on Informatica as whole n integration of different Informatica components n services b 5 yrs of exp in install,configure,admin,tune n troubleshoot 1 or more Informatica ie IDQ, MDM, BDM, BDQ, EDC,or AXON c understanding of data governance n exp on data quality development n issue mgmt Professional Attributes : a Complete understanding of code promotion activities n best practices b Good communication and presentations skills and ability to lead meetings effectively c Ability to multi task with strong attention to detail n analytical skills Educational Qualification : Graduate 15 years of full time education
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Aliases — catalog
- Informatica (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Data Integration Platform
- Vendor
- Informatica
- License
- proprietary
- Year introduced
- 1993
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Informatica appears frequently in enterprise data-integration and ETL job postings, especially alongside cloud migration and MDM roles; it remains a common hiring keyword rather than a sunset technology.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 114
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
ETL and ELT Tooling Catalog dimension db id 24
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
ETL and ELT Tooling
etl-and-elt-tooling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
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
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
- 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
- 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
All API 3 persistence rows
Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.
| Skill | Tag | Dimension | Skill↔dim | Role↔dim | Outcome | Notes |
|---|---|---|---|---|---|---|
| Informatica | in_db |
ETL and ELT Tooling
etl-and-elt-tooling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | IDQ | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | MDM | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | BDM | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | BDQ | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | EDC | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Axon | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | ETL | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "Accenture is a global professional",
"last_5_words": "value and shared success for our clients"
},
"text": "Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Interactive, Technology and Operations services-all powered by the world\u0027s largest network of Advanced Technology and Intelligent Operations centers. Our 674,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries.We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.",
"word_count": 84
},
"certifications": [],
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"ITES",
"BPO",
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],
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},
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},
"education": [
{
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"qualification": "Graduate",
"raw": "Graduate",
"requirement": "required"
}
],
"experience": {
"max": 6,
"min": 4,
"raw": "4-6 years"
},
"job_locations": [
{
"aliases": [
"Pune, Maharashtra"
],
"city": "Pune",
"country": "India",
"state": null,
"work_mode": "null"
}
],
"role": "Application Developer",
"role_aliases": [
"App Developer",
"Software Developer",
"Application Engineer"
],
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"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Key Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "a Design, develop, test, deploy",
"last_5_words": "how to proceed with backend ETL processes"
},
"text": "a Design, develop, test, deploy and document a projects data quality procedures and its outputs b Document at a functional level how the procedures work within the data quality applications c The primary tasks associated with this role are to use IDQ to profile the project source data, define or confirm the definition of the metadata, cleanse and accurately check the project data, check for duplicate or redundant records, and provide information on how to proceed with backend ETL processes",
"word_count": 64
},
{
"bullet_count": 0,
"heading": "Must Have Skills",
"heading_was_present": true,
"source_marker": {
"first_5_words": "",
"last_5_words": ""
},
"text": "",
"word_count": 0
},
{
"bullet_count": 0,
"heading": "Good To Have Skills",
"heading_was_present": true,
"source_marker": {
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"last_5_words": ""
},
"text": "",
"word_count": 0
},
{
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"heading": "Job Requirements",
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"source_marker": {
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},
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"word_count": 0
},
{
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"heading_was_present": true,
"source_marker": {
"first_5_words": "a knowledge on Informatica as",
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},
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},
{
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"source_marker": {
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"last_5_words": "n analytical skills"
},
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"word_count": 36
}
],
"urls": [
{
"type": "website",
"url": "www.accenture.com"
}
]
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Informatica"
},
{
"is_primary": true,
"skill_name": "IDQ"
},
{
"is_primary": true,
"skill_name": "MDM"
},
{
"is_primary": true,
"skill_name": "BDM"
},
{
"is_primary": true,
"skill_name": "BDQ"
},
{
"is_primary": true,
"skill_name": "EDC"
},
{
"is_primary": true,
"skill_name": "Axon"
},
{
"is_primary": true,
"skill_name": "ETL"
}
],
"jd_role": {
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"rationale": null,
"role_aliases": [
"App Developer",
"Software Developer",
"Application Engineer"
],
"role_archetype": "Engineering",
"slug": ""
},
"nano_parsed": {
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},
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],
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},
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},
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{
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"raw": "Graduate",
"requirement": "required"
}
],
"experience": {
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},
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{
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],
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"state": null,
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}
],
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},
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},
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"source_marker": {
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},
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}
],
"urls": [
{
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}
]
},
"rejected": false,
"rejection_reason": null,
"run_id": "536e62f4-6cbe-490e-a83c-c17c835fe278",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
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"kra_matches": null,
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"matched_skills": null,
"role_id": 1,
"score": 1.0,
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"total_count": null
}
],
"kra_match_roles": [
{
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{
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{
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{
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},
{
"display_name": "Angular Frontend Developer",
"kra_matches": [
{
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"similarity": 0.4988
},
{
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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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},
{
"display_name": "Pega Developer",
"kra_matches": [
{
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"sentence": "a Design, develop, test, deploy and document a projects data quality procedures and its outputs b Document at a functional level how the procedures work within the data quality applications c The primary tasks associated with this role are to use IDQ to profile the project source data, define or confirm the definition of the metadata, cleanse and accurately check the project data, check for duplicate or redundant records, and provide information on how to proceed with backend ETL processes",
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},
{
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},
{
"kra_text": "exception, escalation, and assignment handling",
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}
],
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}
],
"skill_match_roles": [
{
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"matched_count": 1,
"matched_skills": [
"Informatica"
],
"role_id": 2,
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"slug": "data-engineer",
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}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "A",
"chosen_role": {
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"role_id": 1,
"score": 1.0,
"slug": "backend-engineer",
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},
"confidence": 1.0,
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"llm2_fired": false,
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"matched_dimensions": [],
"matched_kras": [],
"matched_skills": [],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Exact alias hit on backend-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.12 does not contradict",
"sub_role": null
},
"stage5_updates": {
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"collision_log_id": null,
"new_kra_attached": {
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"r_and_r_preview": "a Design, develop, test, deploy and document a projects data quality procedures and its outputs b Document at a functional level how the procedures work within the data quality applications c The prim",
"role_display_name": "Backend Developer",
"role_slug": "backend-engineer",
"status": "pending"
},
"new_skills_attached": [
{
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"role_display_name": "Backend Developer",
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},
{
"is_primary": true,
"queue_id": 24564,
"role_display_name": "Backend Developer",
"role_slug": "backend-engineer",
"skill_name": "MDM",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 24565,
"role_display_name": "Backend Developer",
"role_slug": "backend-engineer",
"skill_name": "BDM",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 24566,
"role_display_name": "Backend Developer",
"role_slug": "backend-engineer",
"skill_name": "BDQ",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 24567,
"role_display_name": "Backend Developer",
"role_slug": "backend-engineer",
"skill_name": "EDC",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 24568,
"role_display_name": "Backend Developer",
"role_slug": "backend-engineer",
"skill_name": "Axon",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 24569,
"role_display_name": "Backend Developer",
"role_slug": "backend-engineer",
"skill_name": "ETL",
"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": 311,
"existing_alias_text": "Informatica",
"input_term": "Informatica",
"matched_canonical": {
"category_id": 9,
"display_name": "Informatica",
"id": 117,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "informatica",
"sub_category_id": 114,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
}
],
"candidate_roles": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"chosen_role": {
"display_name": "Backend Developer",
"id": 1,
"rationale": "Exact alias hit on backend-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.12 does not contradict",
"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"
},
"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": "Informatica",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_final_skills": [
"Informatica",
"IDQ",
"MDM",
"BDM",
"BDQ",
"EDC",
"Axon",
"ETL"
],
"input_llm_skills": [
"Informatica",
"IDQ",
"MDM",
"BDM",
"BDQ",
"EDC",
"Axon",
"ETL"
],
"new_aliases_persisted": 0,
"run_id": "536e62f4-6cbe-490e-a83c-c17c835fe278",
"skills_detail": [
{
"aliases_in_db": [
{
"alias_text": "Informatica",
"alias_type": "CANONICAL",
"id": 311,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 9,
"display_name": "Informatica",
"id": 117,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PLATFORM",
"slug": "informatica",
"sub_category_id": 114,
"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": "Informatica",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_skill": "Informatica",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "IDQ",
"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": "idq",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "MDM",
"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": "mdm",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "BDM",
"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": "bdm",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "BDQ",
"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": "bdq",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "EDC",
"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": "edc",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Axon",
"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": "axon",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"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": "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": "etl",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"IDQ",
"MDM",
"BDM",
"BDQ",
"EDC",
"Axon",
"ETL"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Backend Developer",
"id": 1,
"rationale": "Exact alias hit on backend-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.12 does not contradict",
"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"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Informatica",
"tag": "in_db"
},
{
"skill": "IDQ",
"tag": "new"
},
{
"skill": "MDM",
"tag": "new"
},
{
"skill": "BDM",
"tag": "new"
},
{
"skill": "BDQ",
"tag": "new"
},
{
"skill": "EDC",
"tag": "new"
},
{
"skill": "Axon",
"tag": "new"
},
{
"skill": "ETL",
"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": 1,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "ETL and ELT Tooling",
"id": 24,
"rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
"slug": "etl-and-elt-tooling",
"source": "db"
},
"dimension_id": 24,
"input_skill": "Informatica",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 117,
"skill_tag": "in_db",
"skipped_reason": null
}
],
"new_skills_created": 0,
"role_dimension_saved": 0,
"skill_dimension_saved": 0,
"skipped": 0
},
"planner_output": null,
"run_id": "536e62f4-6cbe-490e-a83c-c17c835fe278"
}