Job Information

The Data and AI Governance Manager is a leadership role responsible for designing, embedding, and continuously maturing the enterprise-wide framework that governs how data and AI are sourced, managed, protected and deployed across the organization.

Operating at the intersection of data strategy, AI risk, and regulatory compliance within a highly regulated financial services environment, the role ensures the organization's practices align with industry standards including DCAM, NIST AI RMF and ISO 42001, while proactively managing emerging AI and data risks.

The manager works in close relationships with Data & AI engineering, Risk & Compliance, Legal and Business Units to translate policies into operational practices and embed a culture of responsible data and AI use. Reporting directly to the VP, Data and AI, this role plays a pivotal part in shaping the organization’s governance posture as it scales its AI capabilities and navigates on evolving regulatory landscape.

Key Job Functions

• Strategy & Framework Design

  • Lead the design, implementation, and continuous improvement of the enterprise Data & AI Governance framework, aligned to DCAM maturity levels, NIST AI RMF core functions, and ISO 42001 requirements.
  • Own & Direct the development and lifecycle management of data governance policies, AI governance standards, data quality rules, and metadata management practices across all business domains.
  • Partner in driving the organization's AI governance roadmap, ensuring AI systems are inventoried, risk-classified, and governed through structured review and approval processes prior to deployment.
  • Define and maintain a clear governance operating model, including data stewardship accountabilities, decision rights, escalation paths, and governance council structures.
  • Explore and integrate emerging technologies, including AI, to streamline governance workflows, improve metadata curation and strengthen quality and compliance monitoring.

  Risk, Compliance & Regulatory Alignment

  • Ensure ongoing alignment with FHFA and other relevant regulations and emerging AI-specific regulatory requirements across all jurisdictions of operation.
  • Partner with Risk, Compliance, Legal, and Internal Audit teams to identify data and AI-related risks, define controls, and ensure gaps are tracked and remediated in a timely manner.
  • Monitor the organization's DCAM assessment scores and NIST AI RMF profile, conducting periodic gap analyses and preparing executive-level maturity reports for the VP, Data & AI and senior stakeholders.
  • Champion responsible and ethical AI practices, including fairness, explainability, transparency, and accountability requirements in alignment with ISO 42001 and internal AI ethics principles.

  Data Quality & Stewardship

  • Establish and embed enterprise data quality standards and measurement frameworks, working with Data Stewards across business domains to drive accountability and remediation.
  • Oversee data classification, critical data element identification, metadata management, and Collibra DIC management to ensure consistent governance across all data domains.
  • Facilitate the Data Governance Council and domain stewardship forums, preparing agenda, tracking actions, and ensuring governance decisions are documented and communicated effectively.

  Stakeholder Engagement & Culture

  • Collaborate with senior leaders across Business, Finance, Risk, Technology, and Legal & Compliance to gain buy-in, embed governance accountabilities, and resolve cross-functional data and AI governance issues.
  • Advocate for a data-literate and AI-responsible culture by developing awareness programs, training curricula, and communication strategies that build governance knowledge across the organization.
  • Influence product and technology decisions by providing governance counsel during the design and procurement of data systems, AI platforms, and third-party AI tools.

  Team Leadership & Development

  • Manage & Develop a high-performing team of five governance professionals, setting clear objectives, providing coaching, conducting performance reviews, and fostering an inclusive and collaborative team culture.
  • Allocate team capacity and resources effectively across governance tasks and initiatives, ensuring delivery against agreed milestones and outcomes.
  • Mentor team members on data governance methodologies, AI risk concepts, and industry frameworks to build internal capability and career growth.
  • Develop and manage the annual budget for the data governance team, optimizing investment across tools - for example metrics dashboard, AWS expenses, training etc.

  Reporting & Performance Metrics

  • Define and maintain a suite of governance KPIs and KRIs (e.g., data quality scores, AI risk incident rates, policy compliance rates, stewardship coverage) reported to the VP, Data & AI on a regular basis.