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Lead Data Engineer

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Hybrid

Lead Data Engineer

Themathcompany

Lead Data Engineer

Skills

Google Cloud PlatformData EngineeringDatabricksAWSGitHubProcess ImprovementComplianceTerraformAzure

25 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

24 September 2026

What they need


Role & responsibilities

Job Responsibilities

  • Responsible for leading a team of talented data engineers responsible for designing, building, and maintaining scalable data pipelines and infrastructure
  • Work closely with cross-functional teams to ensure client data systems meet the highest standards of quality and performance
  • Lead, mentor, and develop a team of data engineers, fostering a collaborative and inclusive team environment
  • Conduct regular performance reviews, provide feedback, and set goals for team members
  • Identify and address skill gaps, and provide opportunities for professional development
  • Plan, execute, and deliver data engineering projects on time and within scope
  • Coordinate with stakeholders to gather requirements, set priorities, and define project timelines.
  • Ensure projects align with overall business objectives and data strategy
  • Oversee the design, development, and maintenance of data pipelines, ETL processes, and data warehouse
  • Ensure data quality, integrity, and security across all data engineering projects. •
  • Identify opportunities for process improvements and drive initiatives to enhance the efficiency and effectiveness of data operations.
  • Has strong conceptual understanding of Data Warehousing and ETL, Data Governance and Security, Cloud Computing, and Batch & Real Time data processing
  • Ability to build/drive reusable frameworks that can drive efficiency of the overall data system
  • Has executed and lead multiple projects including on - streaming, batch, large data pipelines, etc.
  • Manages conversation with the client stakeholders to understand the Internal Use Only requirement and translate it into technical outcomes.

Preferred candidate profile

  • Strong experience with Databricks, Spark, and cloud platforms (Azure, AWS, GCP).
  • Architect and deploy cloud-based data solutions (Azure, AWS, GCP).
  • Define CI/CD strategies for data pipelines using Terraform, Azure DevOps, or GitHub Actions.
  • Implement data cataloging, lineage tracking, and access control (Unity Catalog, Collibra, Alation).
  • Ensure compliance with GDPR, CCPA, and industry-specific data security policies.
  • Develop strategies for distributed computing, parallel processing, and caching mechanisms.

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