Job Description

We are seeking a Data Governance Engineer to design and implement scalable data governance, quality, security, and compliance capabilities across modern 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 / GenAI Governance Enablement

• Enable responsible AI and GenAI governance by:
• Ensuring trusted, high‑quality data inputs
• Applying secure access and privacy controls
• Supporting lineage and explainability for AI/ML data pipelines
• Collaborate with AI/ML teams leveraging SageMaker and Amazon Bedrock.

Automation & DevOps

• Automate governance, quality, and compliance checks using CI/CD pipelines.
• Implement infrastructure‑as‑code for governance configurations where applicable.
• Integrate monitoring, logging, and alerting for governance controls.

Collaboration & Stakeholder Engagement

• Work closely with data engineers, architects, data scientists, compliance, and business stakeholders.
• Educate teams on governance standards and best practices.
• Assist data owners and stewards with onboarding governed datasets.

Required Skills & Experience

Technical Skills

• Strong experience with SQL and Python.
• Hands‑on experience with Databricks and Snowflake.
• Proven experience with AWS and/or Azure data platforms.
• Experience implementing:
• Data catalogs, metadata, and lineage
• Data quality frameworks
• Data security and access controls
• Familiarity with ML / AI platforms (SageMaker, Bedrock) from a data governance perspective.
• Understanding of data architecture, ETL/ELT workflows, and analytics pipelines.
• Experience with DevOps and automation concepts.

Soft Skills

• Strong analytical and problem‑solving skills.
• Excellent communication skills with both technical and non‑technical audiences.
• Ability to influence data practices across teams.
• Detail‑oriented with a strong focus on risk mitigation and data trust.

Education Requirements

Bachelor’s degree in Computer Science, Data Management, Information Systems, Engineering, or a related field.

Master’s degree is a plus.

Experience Requirements

5+ years of experience in data engineering, data governance, or data management roles.

3+ years of hands‑on experience in cloud data platforms (AWS and/or Azure).

Experience supporting enterprise‑scale analytics, reporting, and AI initiatives.

Preferred Qualifications

Certifications in AWS, Azure, Databricks, Snowflake, or Data Governance.

Experience in regulated industries (healthcare, life sciences, finance).

Familiarity with privacy, security, and compliance frameworks.

Experience supporting governed data for GenAI initiatives.