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Pipeline run

a859e1cb-3b53-4499-ac76-ec2d2c6dcbf6

Pipeline LLM cost (USD)
API 1: $0.0073 API 2: $0.0002 API 3: $0.0000 Total: $0.0075

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 platform optimization and governance
Lead client-facing data engineering engagements end to end: translate business needs into solution architecture, manage budgets/timelines and a 8–12 engineer team, and drive presales/RFPs while enforcing quality, security, and compliance.
"Architect scalable data solutions; enforce best practices in quality, security, and compliance."
Tech stack maturity
Mainstream Modern
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 Engineering Solution Architecture Presales RFPs
Skill cluster (1 dimension groups, role-scoped)
Cross-cutting / unaligned
Data Engineering Solution Architecture Presales RFPs
Show KRA description ↓
• B.E./B.Tech. in Computer Science, IT, or related field • 8–12 years in Data Engineering, including 3+ years in team or project leadership roles • Proven track record in delivering client-facing data solutions in consulting or IT services • Experience in presales, solution architecture, and budgeting • Deep understanding of enterprise data ecosystems and business processes • Exceptional communication, stakeholder management, and problem-solving skills • Client Engagement: Serve as the main client liaison, translating business goals into technical strategies; ensure satisfaction through clear communication and quality delivery. • Project Delivery: Lead end-to-end data engineering projects, manage budgets, timelines, and align cross-functional teams. • Technical Leadership: Architect scalable data solutions; enforce best practices in quality, security, and compliance. • Team Management: Mentor and manage a team of 8–12 engineers; foster a high-performing, collaborative culture. • Consulting & Growth: Drive presales, solutioning, and RFPs; represent the firm in webinars and thought leadership.

Signals

Skill
Alias data-engineer
1.00
KRA data-engineer
0.52

Post-classification

Centroidupdated · n=64
Alias collision log
New-role queue
New skills captured4
New KRA captured

Captured for admin review

Data Engineering primary Data Engineer pending
Solution Architecture primary Data Engineer pending
Presales primary Data Engineer pending
RFPs primary Data Engineer pending
Status: completed Created: 2026-05-27T13:40:59.625891Z Updated: 2026-05-27T13:42:13.963912Z API 3 duration: 1922 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 leading end-to-end data engineering delivery, solution architecture, team management, and client-facing consulting work, which best matches Data Engineer among the candidates.

Matched skills

Data Engineeringsolution architecturebudgetingenterprise data ecosystemsbusiness processesstakeholder managementpresalesRFPs

Matched dimensions

Client-facing data solution deliveryTechnical leadership and architectureProject and budget managementTeam management and mentoringConsulting and presales support

Matched KRAs

Serve as the main client liaisonLead end-to-end data engineering projectsManage budgets, timelines, and cross-functional teamsArchitect scalable data solutionsEnforce best practices in quality, security, and complianceMentor and manage a team of 8–12 engineersDrive presales, solutioning, and RFPs

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

Work Type: Full-time | Hybrid | Working Hours: IST with some US overlap

Location: Hyderabad, India

Compensation (Yearly): ₹3,000,000 – ₹3,700,000

Note: If shortlisted, we will reach out to you via WhatsApp and email. Please respond promptly.

About The Client

• Our client is a fast-growing consulting partner driving enterprise-level data modernization and transformation projects. With a strong focus on delivering measurable business impact, they specialize in cloud data engineering, architecture consulting, and digital modernization for global clients.


About The Role

• We are seeking a Manager – Data Engineering with a consulting mindset, strong leadership qualities, and expertise in solutioning, presales, and project execution. This role will involve direct client engagement, team management, and end-to-end delivery of enterprise data engineering projects. You will oversee technical strategy, ensure timely project delivery, and support business development initiatives.


Must-Have Qualifications

• B.E./B.Tech. in Computer Science, IT, or related field
• 8–12 years in Data Engineering, including 3+ years in team or project leadership roles
• Proven track record in delivering client-facing data solutions in consulting or IT services
• Experience in presales, solution architecture, and budgeting
• Deep understanding of enterprise data ecosystems and business processes
• Exceptional communication, stakeholder management, and problem-solving skills


Preferred Industry Exposure

• Consulting | IT Services | Data & Analytics Firms | Enterprise SaaS | Digital Transformation Agencies


Key Responsibilities (Shortened)

• Client Engagement: Serve as the main client liaison, translating business goals into technical strategies; ensure satisfaction through clear communication and quality delivery.
• Project Delivery: Lead end-to-end data engineering projects, manage budgets, timelines, and align cross-functional teams.
• Technical Leadership: Architect scalable data solutions; enforce best practices in quality, security, and compliance.
• Team Management: Mentor and manage a team of 8–12 engineers; foster a high-performing, collaborative culture.
• Consulting & Growth: Drive presales, solutioning, and RFPs; represent the firm in webinars and thought leadership.

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 Engineering 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
Solution Architecture 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
Architectural Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Presales 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
Soft Skills
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
RFPs 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
Soft Skills
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Data Engineering | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Solution Architecture | type=Architectural Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Presales | type=Soft Skills subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed RFPs | type=Soft Skills subtype=general nature=PRACTICE lifespan=MULTI_YEAR
nano JD Parser — gpt-4.1-nano click to toggle
RoleManager – Data Engineering
CompanyOur client
Experience8–12 years in Data Engineering, including 3+ years in team or project leadership roles
CTC{'max': 3700000, 'min': 3000000, 'raw': '₹3,000,000 – ₹3,700,000', 'period': 'annual', 'currency': 'INR'}
DomainIT Services & Consulting
Location Hyderabad, India (hybrid)
JD type pass
Show raw JSON
{
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    "word_count": 42
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  "archetype_override_applied": true,
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      "word_count": 83
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
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      "is_primary": true,
      "skill_name": "Data Engineering"
    },
    {
      "is_primary": true,
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  "stage3_signals": {
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    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
API 2 — extract-details
{
  "alias_matches": [],
  "candidate_roles": [],
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on leading end-to-end data engineering delivery, solution architecture, team management, and client-facing consulting work, which best matches Data Engineer among the candidates.",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "dimensions": [],
  "input_final_skills": [
    "Data Engineering",
    "Solution Architecture",
    "Presales",
    "RFPs"
  ],
  "input_llm_skills": [
    "Data Engineering",
    "Solution Architecture",
    "Presales",
    "RFPs"
  ],
  "new_aliases_persisted": 0,
  "run_id": "a859e1cb-3b53-4499-ac76-ec2d2c6dcbf6",
  "skills_detail": [
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Data Engineering",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "PRACTICE",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "data-engineering",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Solution Architecture",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Architectural Concepts",
          "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": "solution-architecture",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Presales",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Soft Skills",
          "skill_nature": "PRACTICE",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "presales",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "RFPs",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Soft Skills",
          "skill_nature": "PRACTICE",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "rfps",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Data Engineering",
    "Solution Architecture",
    "Presales",
    "RFPs"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on leading end-to-end data engineering delivery, solution architecture, team management, and client-facing consulting work, which best matches Data Engineer among the candidates.",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Data Engineering",
      "tag": "new"
    },
    {
      "skill": "Solution Architecture",
      "tag": "new"
    },
    {
      "skill": "Presales",
      "tag": "new"
    },
    {
      "skill": "RFPs",
      "tag": "new"
    }
  ],
  "llm_cost_api1_usd": null,
  "llm_cost_api2_usd": null,
  "llm_cost_api3_usd": null,
  "llm_cost_total_usd": null,
  "persistence": {
    "items": [],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 0
  },
  "planner_output": null,
  "run_id": "a859e1cb-3b53-4499-ac76-ec2d2c6dcbf6"
}

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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