Company
SrGovernanceEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Sr Governance Engineer. Skills: Data Governance, Cloud Data Platforms, Data Security, Data Quality. Design data governance frameworks. Implement data governance frameworks”
Industry & Context.
Analytical; Problem-solving; Root cause analysis
What They're Looking For.
Must Have
5+ years experience, 3+ years cloud experience, Bachelor's degree
Nice to Have
Master's degree is a plus, Certifications in AWS, Azure, Databricks, Snowflake, or Data Governance, Experience in regulated industries, Familiarity with privacy, security, and compliance frameworks, Experience supporting governed data for GenAI initiatives
What You'll Do.
Design data governance frameworks
Implement data governance frameworks
Translate requirements into controls
Define data standards
Manage data standards
Define documentation practices
Manage documentation practices
Implement data catalogs
Implement metadata management
Manage metadata management
Implement business glossaries
Manage business glossaries
Ensure metadata coverage
Design data quality rules
Implement data quality rules
Design data quality checks
Implement data quality checks
Design data quality monitoring
Implement data quality monitoring
Integrate data quality validation
Define data reliability SLAs
Define data trustworthiness metrics
Support root cause analysis
Support remediation of data quality issues
Implement data classification
Implement data masking
Implement data tokenization
Implement data encryption
Enforce access control
Ensure regulatory compliance
Ensure privacy compliance
Support secure data access
Define governance controls
Enforce governance controls
Audit policy compliance
Enable responsible AI governance
Enable GenAI governance
Apply secure access controls
Apply privacy controls
Support lineage for AI/ML
Support explainability for AI/ML
Automate governance checks
Automate quality checks
Automate compliance checks
Implement infrastructure-as-code
Integrate monitoring for controls
Integrate logging for controls
Integrate alerting for controls
Work with data engineers
Work with data scientists
Work with compliance teams
Work with business stakeholders
Educate teams on standards
Educate teams on best practices
Assist data owners with onboarding
Assist data stewards with onboarding
How You'll Work.
Team & Collaboration
Data engineering teams; Analytics teams; AI/ML teams; Compliance teams; Platform teams; AI/ML teams; Data engineers; Architects; Data scientists; Compliance; Business stakeholders; Data owners; Data stewards
Communication Scope
Technical audiences; Non-technical audiences
Process & Methodology
DevOps, Automation
Full Job Description
**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 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 dat
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