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Pipeline run

85d78cb4-f290-40a0-bc47-4abec9c25362

Pipeline LLM cost (USD)
API 1: $0.0069 API 2: $0.0001 API 3: $0.0000 Total: $0.0070

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
SPARSE JD role baseline loaded sources · ai_index: role_baseline · nature_of_work: jd · tech_stack_maturity: jd
Nature of work · Data transformation and modeling
Works with analytics, business, and engineering teams to improve BI data models, monitor and fix data quality issues, and use analysis, tests, and documentation to keep production data accurate and available.
"Collaborates with analytics and business teams to improve data models that feed business intelligence tools"
Tech stack maturity
Mainstream Modern
Data engineering roles centered on integration and unit testing typically align with established, widely adopted modern practices rather than bleeding-edge or legacy-only stacks.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
1.20 / 5
· Title match
· Has AI skill
· AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3):
Evidence — skills matched in JD (4)
Data Analysis Unit Testing Integration Testing Business Intelligence
Skill cluster (2 dimension groups, role-scoped)
Testing and Quality Assurance
Integration Testing
Cross-cutting / unaligned
Data Analysis Unit Testing Business Intelligence
Show KRA description ↓
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. Qualification Required-Diploma,B.tech,M.tech,IT,Engineering,ITI,

Signals

Skill backend-engineer
0.25
Alias data-engineer
1.00
KRA data-engineer
0.65

Post-classification

Centroidupdated · n=272
Alias collision log
New-role queue
New skills captured2
New KRA captured

Captured for admin review

Data Analysis primary Data Engineer pending
Business Intelligence primary Data Engineer pending
Status: completed Created: 2026-05-27T15:16:31.377615Z Updated: 2026-06-12T16:42:01.817038Z API 3 duration: 13140 ms
Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

Data Engineer

domain · Data Engineering & Analytics CASE DOMAIN

slug: 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

data modelsdata qualityunit/integration testsengineering wikidata analysis

Matched dimensions

Data ModelingData Quality MonitoringData Pipeline SupportData TroubleshootingCross-functional CollaborationDocumentation and Testing

Matched KRAs

Improve data models that feed business intelligence toolsImplement processes and systems to monitor data qualityEnsure production data is always accurate and availableWrite unit/integration testsContribute to engineering wiki and document workPerform data analysis to troubleshoot data related issues

Resolution: in_db — role exists in library; skill↔dim and role↔dim links saved when applicable.

0
New skills
0
Skill↔dim saved
0
Role↔dim saved
0
Skipped

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.

Data Analysis Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Unit Testing Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Unit Testing id=517 · unit-testing

Aliases — catalog

  • Unit Testing (CANONICAL)

Context tags (catalog)

JUnit NUnit TDD arrange-act-assert assertions code coverage fixtures mocking pytest regression stubs test cases test doubles test runner xUnit

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)
Integration Testing Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Integration testing id=56 · integration-testing

Aliases — catalog

  • Integration testing (CANONICAL) primary
  • integration testing (CANONICAL)

Context tags (catalog)

API testing CI/CD Cucumber JUnit Selenium behavior-driven development continuous integration contract testing end-to-end end-to-end testing fixtures mocking pytest quality assurance regression testing smoke testing stubs system testing test automation test cases test coverage test data test frameworks test harness test strategy test suite test-driven development

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)
Business Intelligence Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
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
RoleData Engineer
Experience0 To 4
CTC{'max': 75, 'min': 48, 'raw': 'Salary-48K To 75k', 'period': 'monthly', 'currency': 'INR'}
DomainIT Services & Consulting
JD type pass
Show raw JSON
{
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  "experience": {
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    "min": 0,
    "raw": "0 To 4"
  },
  "job_locations": [],
  "role": "Data Engineer",
  "role_aliases": [
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      "text": "Qualification Required-Diploma,B.tech,M.tech,IT,Engineering,ITI,",
      "word_count": 8
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  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
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      "is_primary": true,
      "skill_name": "Data Analysis"
    },
    {
      "is_primary": true,
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  "rejection_reason": null,
  "run_id": "85d78cb4-f290-40a0-bc47-4abec9c25362",
  "stage3_signals": {
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    "kra_match_roles": [
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    "case": "DOMAIN",
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    "llm2_reasoning": null,
    "matched_dimensions": [
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      "Data Quality Monitoring",
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      "Implement processes and systems to monitor data quality",
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      "Perform data analysis to troubleshoot data related issues"
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    "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
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    "centroid_updated": true,
    "collision_log_id": null,
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}
API 2 — extract-details
{
  "alias_matches": [
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 865,
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      "matched_via": "alias"
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    }
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      "role_archetype": null,
      "slug": "pega-developer",
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    {
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      "role_archetype": "Engineering",
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    },
    {
      "display_name": "Backend Developer",
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      "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.",
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    {
      "display_name": "PHP Backend Developer",
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      "role_archetype": "Engineering",
      "slug": "php-backend-developer",
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      "display_name": "Python Backend Developer",
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    },
    {
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      "rationale": null,
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      "slug": "scala-backend-developer",
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  ],
  "chosen_role": {
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    "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": [
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      "dimension": {
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      },
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      "roles_from_db": []
    },
    {
      "dimension": {
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    },
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        },
        {
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          "rationale": null,
          "role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
          "slug": "backend-engineer",
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        },
        {
          "display_name": "Node.js Backend Developer",
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          "rationale": null,
          "role_archetype": "Engineering",
          "slug": "node-backend-developer",
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        },
        {
          "display_name": "PHP Backend Developer",
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        },
        {
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          "rationale": null,
          "role_archetype": "Engineering",
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        },
        {
          "display_name": "Scala Backend Developer",
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          "slug": "scala-backend-developer",
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        }
      ]
    }
  ],
  "input_final_skills": [
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  "input_llm_skills": [
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    "Integration Testing",
    "Business Intelligence"
  ],
  "new_aliases_persisted": 0,
  "run_id": "85d78cb4-f290-40a0-bc47-4abec9c25362",
  "skills_detail": [
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      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
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      "new_alias_text": null,
      "new_skill_meta": {
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      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Unit Testing",
          "alias_type": "CANONICAL",
          "id": 865,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
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      },
      "dimensions": [
        {
          "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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              "slug": "python-backend-developer",
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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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  "chosen_role_resolution": "in_db",
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      "skill": "Data Analysis",
      "tag": "new"
    },
    {
      "skill": "Unit Testing",
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    },
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      "skill": "Integration Testing",
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    {
      "skill": "Business Intelligence",
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  "llm_cost_api2_usd": null,
  "llm_cost_api3_usd": null,
  "llm_cost_total_usd": null,
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        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
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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.

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