AI Governance Engineer Remote

AI Governance Engineer

or ship Required

6 months c2h (Contract to Hire) Position

We are seeking an experienced AI Governance Professional to support enterprise AI, data governance, and operational modernization initiatives. This role will be responsible for maintaining and enhancing AI governance processes, managing metadata through Alation, leveraging AWS cloud services, and ensuring enterprise data assets are properly cataloged, governed, and accessible for AI and analytics use cases.
The ideal candidate possesses strong experience with Alation Data Catalog, AWS data services, Python scripting, and modern data operations practices. This individual will collaborate with data engineering, cloud, analytics, governance, security, and business teams to improve metadata management, automation, lineage, compliance, and operational efficiency.

Key Responsibilities AI & Data Governance

• Administer and support enterprise AI Governance and Data Governance programs.
• Manage and maintain metadata repositories, business glossaries, data lineage, classifications, and governance policies within Alation.
• Configure and optimize Alation data sources, metadata ingestion processes, stewardship workflows, and governance controls.
• Partner with data owners and stewards to ensure data quality, compliance, and proper documentation.
• Support AI model governance by documenting data sources, lineage, ownership, and usage controls.
• Develop governance standards, procedures, and best practices for AI and enterprise data assets.
• Coordinate governance reviews and support audit readiness efforts.

Alation Administration & Configuration

• Perform Alation platform configuration and administration.
• Troubleshoot metadata ingestion and cataloging issues.
• Manage source connections and data source synchronization.
• Configure custom metadata attributes, workflows, user roles, and permissions.
• Support integration between Alation and enterprise data platforms.
• Enhance catalog usability and adoption across business and technical stakeholders.

AWS Data & Cloud Operations

• Query, extract, and analyze metadata from AWS services.
• Manage and support:
• AWS Glue
• Amazon S3 Buckets
• AWS Lake Formation
• AWS Data Catalog
• Athena
• IAM Roles and Policies
• Monitor and maintain metadata collection processes across cloud environments.
• Update configurations and permissions as required to support governance and compliance initiatives.
• Support cloud-based data inventory and lineage initiatives.

Data Engineering & Automation

• Develop and maintain Python scripts for:
• Metadata extraction
• Data quality checks
• Governance automation
• Reporting and operational monitoring
• Automate repetitive governance and operational tasks.
• Build integrations between AWS services, Alation, and enterprise governance tools.
• Support API-based metadata harvesting and integration development.

Operations Modernization (Ops Modernization)

• Participate in enterprise Ops Modernization initiatives focused on automation, cloud adoption, and governance maturity.
• Identify opportunities to streamline governance processes through automation and tooling.
• Improve operational efficiency through workflow standardization and data-driven monitoring.
• Support CI/CD and DevOps-aligned governance processes.

Agile & Project Support

• Update and maintain work items, user stories, tasks, and documentation within Azure DevOps (ADO).
• Participate in Agile ceremonies including sprint planning, backlog refinement, stand-ups, and retrospectives.
• Track governance initiatives and operational enhancements through established project management processes.

Metadata & Data Platform Integration

• Support metadata management and lineage initiatives involving:
• AWS Glue Data Catalog
• Ascend
• Bridge/Bridges integrations
• Enterprise data platforms
• Alation metadata connectors
• Validate metadata consistency across multiple systems.
• Assist with onboarding new data assets into governance frameworks.

Required Qualifications

• Bachelor's degree in Information Systems, Computer Science, Data Management, Business Analytics, or related field.
• 3+ years of experience in Data Governance, AI Governance, Data Management, or Metadata Management.
• 2+ years of hands-on experience with Alation.
• Experience administering metadata catalogs and governance platforms.
• Strong experience with AWS cloud services.
• Experience working with:
• AWS Glue
• Amazon S3
• Athena
• IAM
• Data Catalog and metadata management tools
• Strong Python scripting and automation skills.
• Experience querying metadata repositories and cloud data platforms.
• Experience with Azure DevOps (ADO).
• Understanding of data lineage, data quality, metadata, and governance frameworks.
• Strong troubleshooting and analytical skills.

Preferred Qualifications

• Experience supporting AI Governance programs.
• Familiarity with Model Governance and Responsible AI frameworks.
• Experience with Ascend platform integrations.
• Experience with Bridge/Bridges data integration technologies.
• Knowledge of cloud security and compliance controls.
• Experience with enterprise data catalogs and lineage tools.
• AWS Certifications (Solutions Architect, Data Analytics, Cloud Practitioner, or equivalent).
• Alation certification or administrator experience.
• Experience supporting large-scale data modernization initiatives.

Technical Skills Governance & Catalog Tools

• Alation
• Data Catalogs
• Metadata Management
• Data Lineage
• Data Governance
• AI Governance

AWS Technologies

• AWS Glue
• Amazon S3
• Athena
• IAM
• Lake Formation
• CloudWatch
• AWS APIs

Development & Automation

• Python
• SQL
• REST APIs
• JSON
• Shell Scripting

DevOps & Agile

• Azure DevOps (ADO)
• Agile/Scrum
• CI/CD Concepts
• Ops Modernization

Desired Candidate Profile
The ideal candidate is a detail-oriented governance professional who understands both the technical and business aspects of AI and data governance. They are comfortable administering Alation, querying AWS metadata repositories, building Python-based automation, and driving operational modernization efforts while ensuring compliance, transparency, and trust in enterprise data and AI ecosystems.