Data and AI GRC Manager

Overview

Data and AI GRC Manager

Key Responsibilities

• Design, establish, and operationalize the organization's Data and AI Governance framework from a greenfield environment.
• Develop and manage AI governance processes, including AI use-case intake, risk tiering, model risk management, bias and explainability controls, model documentation standards, and oversight of third-party and frontier AI model usage.
• Establish and maintain group-wide data governance standards covering data ownership, stewardship, quality, lineage, metadata management, cataloguing, classification, retention, and lifecycle management.
• Define and implement a data stewardship operating model and enterprise data catalog taxonomy across the group.
• Develop governance processes and controls to support responsible AI adoption and effective data management practices.
• Operationalize compliance with

UAE PDPL (Federal Decree-Law 45/2021)

• and align governance frameworks with the
• EU AI Act, NIST AI Risk Management Framework, ISO/IEC 42001, and ISO/IEC 27001.
• Author and implement AI risk-tiering methodologies, governance processes, and control frameworks.
• Develop model documentation standards and governance requirements for AI, machine learning, and advanced analytics solutions.
• Implement governance controls and processes within platforms such as

Palantir Foundry,

• Microsoft Purview, Microsoft Fabric, and other enterprise governance solutions.
• Establish and facilitate governance forums, working groups, and stakeholder review committees.
• Partner closely with Data and AI, Legal, Risk, Information Security, Enterprise Architecture, and Technology teams to embed governance requirements into data platforms, AI solutions, and business processes.
• Influence stakeholders across the organization to drive governance adoption without direct authority.
• Monitor adherence to governance standards and recommend improvements to strengthen governance maturity.
• Drive awareness, training, and adoption of data and AI governance practices across the organization.

Knowledge, Skills & Experience

• 6–10 years of experience in Data Governance, AI Governance, Data Management, Risk Management, Information Governance, or related disciplines.
• Proven experience designing and implementing governance frameworks, data catalogs, stewardship models, or model risk management processes from inception.
• Strong understanding of data governance principles including data quality, metadata management, lineage, stewardship, classification, retention, and master data management concepts.
• Experience establishing AI governance frameworks covering model risk, explainability, fairness, accountability, and responsible AI practices.
• Demonstrated experience implementing governance controls within enterprise data and governance platforms such as Microsoft Purview, Microsoft Fabric,

Palantir Foundry

• , Collibra, Alation, Informatica, or similar tools.
• Strong understanding of
• UAE PDPL, EU AI Act, NIST AI RMF, ISO/IEC 42001, and ISO/IEC 27001 frameworks and standards.
• Experience working across Legal, Risk, Security, Data, and Technology functions within complex enterprise environments.
• Excellent stakeholder management and influencing skills, with the ability to drive outcomes without direct reporting authority.
• Strong communication, documentation, and facilitation skills with the ability to translate regulatory requirements into practical and scalable controls.
• Experience within real estate, hospitality, financial services, government, or other regulated industries would be advantageous.
• Professional certifications such as
• CDMP, IAPP CIPM, IAPP CIPP/E, ISO/IEC 42001 Lead Implementer
• , or ISO/IEC 27001 Lead Implementer are preferred.
• Bachelor's degree in Information Management, Data Management, Computer Science, Risk Management, Information Security, or a related discipline.

Availability