Senior Manager, Data Governance Engineering

10 years

0 Lacs

Posted:1 week ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Senior Manager of Data Governance Engineering

As a leader within EDB, you will manage and grow a high-performing data engineering team responsible for implementing scalable pipelines for structured and unstructured data, establishing enterprise-wide governance practices, and enabling trusted insights across the organization. You will be the primary driver of our metadata, data dictionary, lineage, and stewardship frameworks, leveraging modern governance and MDM tools.

EDB Postgres and our evolving data lake house architecture


Key Responsibilities

Data Governance Leadership

  • Design, implement, and enforce

    data governance frameworks, policies, and procedures

    that ensure security, compliance, and high data quality.
  • Lead efforts in metadata management, business glossaries, data dictionaries, and

    traceability across systems and workloads

    .
  • Drive stewardship practices to establish data ownership, classification, and accountability.
  • Data Engineering & Pipelines

    • Collaborate in the development of

      scalable, reliable pipelines

      for transactional, analytical, and AI workloads, covering both structured and unstructured data.
    • Ensure pipelines are

      governance-aware

      , embedding validation, quality checks, and lineage capture as part of the process.
    • Partner with analytics, product, and AI teams to build pipelines that power BI dashboards, predictive modeling, and machine learning at scale.


    Tools & Ecosystem Enablement

    • Champion adoption of modern

      data governance and MDM platforms

      (e.g., DataHub) and integrate them with Postgres and lakehouse infrastructure.
    • Evaluate and implement technologies for cataloging, lineage, and observability to ensure transparency and trust.
    • Define and enforce standards for

      documentation, traceability, and reproducibility

      across the data ecosystem.


    Team Leadership & Development

    • Build and lead a

      world-class data engineering team

      focused on governance-aware data engineering.
    • Provide technical guidance, mentorship, and career development opportunities for engineers.
    • Foster a culture of accountability, innovation, and excellence in data practices.


    Business & Compliance Alignment

    • Partner with Compliance, Information Security, and business leaders to align governance with regulatory and strategic needs.
    • Translate governance frameworks into engineering solutions that

      empower business outcomes

      , not just controls.
    • Communicate effectively with executive stakeholders to report on data quality, compliance, and progress against KPIs.


    Required Skills & Experience

    • 10+ years

      of experience in data engineering, data governance, or related roles, with at least

      3–5 years in a leadership/managerial capacity

      .
    • Proven expertise in building and maintaining

      ETL/ELT pipelines

      across structured, unstructured, and semi-structured data including orchestration and automation with tools such as Airflow and data modeling with frameworks like dbt.
    • Strong familiarity with

      data governance and MDM tools

      such as DataHub, Collibra, or Informatica.
    • Hands-on experience with any databases, pref is

      PostgreSQL

      and/or modern data lakehouse platforms (e.g., Databricks, Snowflake, or similar).
    • Strong understanding of

      data governance principles, lineage, metadata, and data privacy regulations

      (e.g., GDPR, CCPA).
    • Track record of

      hiring, developing, and leading engineering teams

      with a focus on delivering measurable outcomes.
    • Excellent stakeholder management and communication skills across technical and business domains.


    Additional Qualifications

    • Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, or related field.
    • Experience supporting

      AI/ML model pipelines

      and governance for AI-driven workloads.
    • Knowledge of

      data quality frameworks

      and tooling for continuous monitoring and improvement.
    • Demonstrated ability to balance

      governance rigor with business agility

      , enabling trusted and efficient outcomes.


    Why This Role Matters

    Senior Manager of Data Governance Engineering

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