Pipeline run
85d78cb4-f290-40a0-bc47-4abec9c25362
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
domain · Data Engineering & Analytics CASE DOMAINslug: data-engineer · id: 2 · source: db
Domain=Data Engineering & Analytics; The JD centers on improving data models, monitoring data quality, troubleshooting data issues, and working with analytics/business teams, which best matches a Data Engineer.
Matched skills
Matched dimensions
Matched KRAs
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
This is your chance to let prospective engineers know what you have to offer new hires and set your posting apart from the rest by catering your recruiting pitch to the ideal candidate. Responsibilities Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization. Implements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it. Writes unit/integration tests, contributes to engineering wiki, and documents work. Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues. Works closely with a team of frontend and backend engineers, product managers, and analysts. Requirements Qualification Required-Diploma,B.tech,M.tech,IT,Engineering,ITI, Benefits Salary-48K To 75k Required Experience-0 To 4 Minimum Age-18 Work Industry-,IT,Banking,Finance Work Department,Data engineer Skills-Technical expertise with data models, data mining, and segmentation techniques for more clarification contact to this number-9911013899 harsheeta.hs1987@gmail.com Regards HR Placement Team This job is provided by Shine.com
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
Aliases — catalog
- Unit Testing (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Testing Methodology
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Unit testing is a standard hiring requirement across software JDs and appears in mainstream frameworks/docs; GitHub and Stack Overflow usage remain consistently high, with no successor replacing it.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 44
- 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
- Integration testing (CANONICAL) primary
- integration testing (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Testing Methodology
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Integration testing is a standard QA skill in job descriptions across backend, frontend, and DevOps roles; it’s commonly paired with CI/CD and tools like Jest, Cypress, and Testcontainers.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 44
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Testing and Defect Resolution Catalog dimension db id 262
Library dimension (catalog)
Roles linked in library: Pega Developer
-
Testing and Quality Assurance Catalog dimension db id 12
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer, Scala Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Testing and Defect Resolution
testing-and-defect-resolution
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Testing and Quality Assurance
testing-and-quality-assurance
|
✓ | — | 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
- 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 |
|---|---|---|---|---|---|---|
| Unit Testing | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Integration Testing | in_db |
Testing and Defect Resolution
testing-and-defect-resolution
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Integration Testing | in_db |
Testing and Quality Assurance
testing-and-quality-assurance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Data Analysis | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Business Intelligence | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
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"about_company": null,
"certifications": [],
"company_name": null,
"ctc": {
"currency": "INR",
"max": 75,
"min": 48,
"period": "monthly",
"raw": "Salary-48K To 75k"
},
"domain": {
"primary": {
"aliases": [
"ITES",
"BPO"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "Diploma/BTECH/BE/MTECH/ME - IT/Engineering",
"raw": "Qualification Required-Diploma,B.tech,M.tech,IT,Engineering,ITI,",
"requirement": "required"
}
],
"experience": {
"max": 4,
"min": 0,
"raw": "0 To 4"
},
"job_locations": [],
"role": "Data Engineer",
"role_aliases": [
"Data Engineer",
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],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
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"heading": "Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Collaborates with analytics and business",
"last_5_words": "product managers, and analysts."
},
"text": "Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization.\nImplements processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.\nWrites unit/integration tests, contributes to engineering wiki, and documents work.\nPerforms data analysis required to troubleshoot data related issues and assist in the resolution of data issues.\nWorks closely with a team of frontend and backend engineers, product managers, and analysts.",
"word_count": 90
},
{
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"source_marker": {
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"last_5_words": "Diploma,B.tech,M.tech,IT,Engineering,ITI,"
},
"text": "Qualification Required-Diploma,B.tech,M.tech,IT,Engineering,ITI,",
"word_count": 8
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Data Analysis"
},
{
"is_primary": true,
"skill_name": "Unit Testing"
},
{
"is_primary": true,
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},
{
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}
],
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"rationale": null,
"role_aliases": [
"Data Engineer",
"Data Analyst"
],
"role_archetype": "Data",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": null,
"certifications": [],
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"ctc": {
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"domain": {
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"ITES",
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],
"experience": {
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},
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},
"text": "Qualification Required-Diploma,B.tech,M.tech,IT,Engineering,ITI,",
"word_count": 8
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "85d78cb4-f290-40a0-bc47-4abec9c25362",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
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},
{
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],
"kra_match_roles": [
{
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"similarity": 0.7228
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{
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{
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],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.6539,
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"total_count": null
},
{
"display_name": "Flutter Developer",
"kra_matches": [
{
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},
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization.",
"similarity": 0.4674
},
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Writes unit/integration tests, contributes to engineering wiki, and documents work.",
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}
],
"matched_count": null,
"matched_skills": null,
"role_id": 74,
"score": 0.5375,
"slug": "flutter-developer",
"total_count": null
},
{
"display_name": "Fullstack Developer",
"kra_matches": [
{
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"sentence": "Works closely with a team of frontend and backend engineers, product managers, and analysts.",
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},
{
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"sentence": "Writes unit/integration tests, contributes to engineering wiki, and documents work.",
"similarity": 0.4586
},
{
"kra_text": "Debugs full-stack issues that span frontend rendering, API behavior, database queries, and infrastructure configuration to identify root causes.",
"sentence": "Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues.",
"similarity": 0.4523
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 15,
"score": 0.5354,
"slug": "full-stack-engineer",
"total_count": null
},
{
"display_name": "Backend Developer",
"kra_matches": [
{
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"sentence": "Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues.",
"similarity": 0.5634
},
{
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"similarity": 0.4916
},
{
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],
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},
{
"display_name": "MLOps Engineer",
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{
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"similarity": 0.5731
},
{
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"similarity": 0.4689
},
{
"kra_text": "Sets up model monitoring dashboards, data drift detection, prediction performance tracking, and alert routing for production ML systems.",
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"similarity": 0.4452
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}
],
"skill_match_roles": [
{
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},
{
"display_name": "Pega Developer",
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"matched_count": 1,
"matched_skills": [
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],
"role_id": 24,
"score": 0.25,
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},
{
"display_name": "Python Backend Developer",
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"Integration testing"
],
"role_id": 80,
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"total_count": 4
},
{
"display_name": "Node.js Backend Developer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Integration testing"
],
"role_id": 82,
"score": 0.25,
"slug": "node-backend-developer",
"total_count": 4
},
{
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"kra_matches": null,
"matched_count": 1,
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"Integration testing"
],
"role_id": 83,
"score": 0.25,
"slug": "dotnet-backend-developer",
"total_count": 4
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "DOMAIN",
"chosen_role": {
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"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.96,
"slug": "data-engineer",
"total_count": null
},
"confidence": 0.96,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [
"Data Modeling",
"Data Quality Monitoring",
"Data Pipeline Support",
"Data Troubleshooting",
"Cross-functional Collaboration",
"Documentation and Testing"
],
"matched_kras": [
"Improve data models that feed business intelligence tools",
"Implement processes and systems to monitor data quality",
"Ensure production data is always accurate and available",
"Write unit/integration tests",
"Contribute to engineering wiki and document work",
"Perform data analysis to troubleshoot data related issues"
],
"matched_skills": [
"data models",
"data quality",
"unit/integration tests",
"engineering wiki",
"data analysis"
],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Domain=Data Engineering \u0026 Analytics; The JD centers on improving data models, monitoring data quality, troubleshooting data issues, and working with analytics/business teams, which best matches a Data Engineer.",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 272,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [
{
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"queue_id": 13483,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Analysis",
"status": "pending"
},
{
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"queue_id": 13485,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Business Intelligence",
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}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{
"alias_matches": [
{
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"alias_persisted": false,
"existing_alias_id": 865,
"existing_alias_text": "Unit Testing",
"input_term": "Unit Testing",
"matched_canonical": {
"category_id": 8,
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"id": 517,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "unit-testing",
"sub_category_id": 44,
"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": 193,
"existing_alias_text": "integration testing",
"input_term": "Integration Testing",
"matched_canonical": {
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"id": 56,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "integration-testing",
"sub_category_id": 44,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
}
],
"candidate_roles": [
{
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"rationale": null,
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"slug": "pega-developer",
"source": "db"
},
{
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"slug": "dotnet-backend-developer",
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},
{
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"slug": "backend-engineer",
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},
{
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},
{
"display_name": "PHP Backend Developer",
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"role_archetype": "Engineering",
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},
{
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"source": "db"
},
{
"display_name": "Scala Backend Developer",
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"rationale": null,
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}
],
"chosen_role": {
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"id": 2,
"rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on improving data models, monitoring data quality, troubleshooting data issues, and working with analytics/business teams, which best matches a Data Engineer.",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "Unit Testing",
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"roles_from_db": []
},
{
"dimension": {
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"display_name": "Testing and Defect Resolution",
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"rationale": "Validates Pega rules, flows, and integrations and then troubleshoots defects found in lower environments or production. This is a coherent cluster because the role is expected to verify platform behavior and fix rule-level issues.",
"slug": "testing-and-defect-resolution",
"source": "db"
},
"input_skill": "Integration Testing",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Pega Developer",
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"slug": "pega-developer",
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}
]
},
{
"dimension": {
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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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}
API 3 — final-role-output
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{
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{
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}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.