Role Overview
We are seeking a Data Governance Engineer to design and implement scalable data governance, quality, security, and compliance capabilities across up-to-date cloud data platforms. This role will work closely with data engineering, analytics, AI/ML, and compliance teams to ensure data is trusted, secure, compliant, and ready for analytics, reporting, and GenAI use cases across AWS and Azure environments.
Key Responsibilities
Data Governance Frameworks & Policy Implementation
Design and implement data governance frameworks covering data ownership, stewardship, classification, retention, and lifecycle management.
Translate business, regulatory, and compliance requirements into enforceable technical controls.
Define and manage data standards, naming conventions, and documentation practices.
Metadata, Lineage & Cataloging
Implement and manage data catalogs, metadata management, and business glossaries.
Enable end‑to‑end data lineage across ingestion, transformation, and consumption layers.
Ensure metadata coverage for datasets in Databricks, Snowflake, S3, and ADLS.




Data Quality Engineering
Design and implement data quality rules, checks, and monitoring frameworks.
Integrate data quality validation into ETL/ELT pipelines.
Define SLAs and metrics for data reliability and trustworthiness.
Support root cause analysis and remediation of data quality issues.
Security, Privacy & Compliance
Implement data classification, masking, tokenization, and encryption strategies.
Enforce role‑based and attribute‑based access control across cloud platforms.
Ensure compliance with regulatory and privacy requirements (e.g., HIPAA, GDPR, internal policies).
Support secure data access for analytics, ML, and GenAI workloads (SageMaker, Bedrock).
Cloud & Platform Governance
Define and enforce governance controls across AWS and Azure data services.
Partner with platform teams to implement guardrails, policies, and controls.
Monitor and audit data access, usage, and policy compliance.
AI

📌 Sr Governance Engineer (Bengaluru)
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