Officer, Data Governance

The Data/AI Governance Officer is responsible for ensuring effective oversight, governance, and compliance of data and AI assets across the enterprise. The role ensures adherence to data governance standards, AI governance principles, regulatory expectations, ethical AI guidelines, and responsible data usage. This includes maintaining data/AI policies, monitoring compliance, supporting AI governance forums, and collaborating with Data Owners, Stewards, and business stakeholders to ensure trust, transparency, and accountability in AI systems.

Responsibilities

Support the implementation of enterprise data governance frameworks, policies, and standards, ensuring alignment with enterprise data strategy, regulatory requirements, and ethical data use; Embed governance structures that not only ensure compliance but also enable innovation, analytics, and AI adoption; Work with Data Owners and Data Stewards to enforce data quality, lineage, classification, and access controls; Support the Data Steward community by ensuring alignment on data quality and defined data quality metrics; Assist with the definition of test cases for data to be executed as part of CTB (change the bank) data requests arising from the labs; Support the development and operationalization of Responsible AI frameworks across the organization; Monitor AI model compliance with fairness, transparency, explainability, and ethical standards; Maintain data and AI governance policies, standards, and procedures; Support Data/AI Governance Councils and Working Groups; Maintain AI model inventories, data governance registers, and asset catalogues; Prepare periodic governance reports, dashboards, and compliance insights

Requirements

Bachelor’s degree in information management, Computer Science, Data Science, Law, Risk Management, or related fields; 3–6+ years of experience in Data Governance, AI Governance, Compliance, Risk Management, or related functions; Experience working with data catalog, metadata, lineage, or data quality tools; Familiarity with AI governance frameworks, risk controls, and regulatory expectations; Experience collaborating with audit, risk, compliance, and technical teams; Adopting Practical Approaches; Articulating Information; Challenging Ideas; Developing Expertise; Documenting Facts; Embracing Change; Interpreting Data; Managing Tasks; Big Data Frameworks and Tools; Data Engineering; Data Integrity; IT Knowledge; Stakeholder Management (IT)

Nice to have

Certifications in Data Governance, Privacy, Risk, or Responsible AI