← Back to history

Pipeline run

97db816a-e687-4ed0-ad12-20536a8efe54

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description

Nature of work

—

no_db_connection

Tech stack maturity

Mainstream Modern

AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)

0.00 / 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 (9)

AWS Azure Databricks SQL Spark Airflow Azure Data Factory DevOps CI/CD

Skill cluster (0 dimension groups, role-scoped)

No dimension groups computed for this JD.

Status: extract_from_jd_done Created: 2026-05-10T13:39:59.343054Z Updated: 2026-05-10T13:39:59.343054Z

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

No chosen role stored for this run.

Job description

Senior Data Engineer – AWS / Azure / Databricks

📍
Location:
Bangalore, India

🏢
Work Model:
On-site

💼
Employment Type:
Contract / Full-time project assignment

📊
Experience:
8–12 years

We are supporting a global technology program seeking an experienced
Senior Data Engineer
to design and build scalable cloud-based data platforms and modern data pipelines within a complex enterprise data environment.

This role focuses on developing robust data engineering solutions that enable advanced analytics and data-driven decision-making across large-scale global operations.

The selected consultant will work closely with data architects, engineers, and business stakeholders to build reliable data foundations and scalable data processing pipelines.

Key Responsibilities

• Design and build
scalable cloud-based data platforms and ELT pipelines

• Develop and maintain
data ingestion, transformation, and integration processes

• Implement
data modeling and data engineering best practices
across enterprise platforms

• Collaborate with business and technology teams to translate
data requirements into scalable solutions

• Optimize data pipelines for
performance, reliability, and cost efficiency
• Support enterprise analytics and reporting capabilities

• Work closely with
data architects, analysts, and engineering teams
to ensure high-quality data solutions

• Contribute to continuous improvement of
data platform architecture and engineering standards

Required Experience
• 8–12 years of experience in Data Engineering or Data Platform roles

• Strong experience building
data pipelines and data integration frameworks

Hands-on experience with
cloud platforms (AWS and/or Azure)

• Experience with
Databricks and modern data engineering tools

• Strong experience with
SQL and large-scale data processing

• Experience working with
enterprise data environments and distributed data systems

Preferred Experience

• Experience working with
Spark or distributed data processing frameworks

• Experience with
data orchestration tools such as Airflow or Azure Data Factory

• Exposure to
DevOps and CI/CD pipelines in data environments

• Experience working in
large global enterprise environments

Engagement Details

•
Location:
Bangalore, India

•
Work Model:
On-site

Skills from this JD

Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.

AWS Primary No API 2 row (run stopped after API 1 or history missing)

Azure Primary No API 2 row (run stopped after API 1 or history missing)

Databricks Primary No API 2 row (run stopped after API 1 or history missing)

SQL Primary No API 2 row (run stopped after API 1 or history missing)

Spark Secondary No API 2 row (run stopped after API 1 or history missing)

Airflow Secondary No API 2 row (run stopped after API 1 or history missing)

Azure Data Factory Secondary No API 2 row (run stopped after API 1 or history missing)

DevOps Secondary No API 2 row (run stopped after API 1 or history missing)

CI/CD Secondary No API 2 row (run stopped after API 1 or history missing)

Library artifacts (this run)

No artifact rows for this run.

API 1 — extract-from-jd click to toggle

{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "AWS"
    },
    {
      "is_primary": true,
      "skill_name": "Azure"
    },
    {
      "is_primary": true,
      "skill_name": "Databricks"
    },
    {
      "is_primary": true,
      "skill_name": "SQL"
    },
    {
      "is_primary": false,
      "skill_name": "Spark"
    },
    {
      "is_primary": false,
      "skill_name": "Airflow"
    },
    {
      "is_primary": false,
      "skill_name": "Azure Data Factory"
    },
    {
      "is_primary": false,
      "skill_name": "DevOps"
    },
    {
      "is_primary": false,
      "skill_name": "CI/CD"
    }
  ],
  "run_id": null
}

API 2 — extract-details

{}

API 3 — final-role-output

{}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

Loading…