Sr Governance Engineer

Role Overview

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 endtoend 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 rolebased and attributebased 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 highquality 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 infrastructureascode 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.
• Handson 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 problemsolving skills.
• Excellent communication skills with both technical and nontechnical audiences.
• Ability to influence data practices across teams.
• Detailoriented with a strong focus on risk mitigation and data trust.

Education Requirements

Bachelors degree in Computer Science Data Management Information Systems Engineering or a related field.

Masters degree is a plus.

Experience Requirements

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

3 years of handson experience in cloud data platforms (AWS and/or Azure).

Experience supporting enterprisescale 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.