Data & AI Governance Officer

JOB SUMMARY

The Data & AI Governance Officer is responsible for shaping, implementing, and championing the organization’s AI and data governance strategy across all platforms. They will act as a technical authority and mentor, driving responsible AI adoption, robust data governance, and operational excellence. The Data & AI Governance Officer will lead Data Engineering, Data Analytics, and partner with cross-functional teams, ensuring a compliant and effective deployment of AI and advanced analytics solutions, while fostering innovation and measurable business value through modern data platforms (e.g., Databricks, Python, cloud data lakes).

• Directs cross-functional teams to establish AI principles focused on fairness, transparency, and explainability, while addressing governance and regulatory issues and promoting accountability and innovation across the organization.
• Develops and executes enterprise data and AI governance strategies aligned with business goals, evolving regulations (OCC, FDIC, Federal Reserve, CFPB), and industry standards.
• Establishes and leads data governance and AI committees to drive cross-functional collaboration and accountability.
• Defines strategic roadmaps for data governance maturity, integrating emerging technologies and regulatory changes.
• Integrates data governance with enterprise architecture and modernization efforts, while ensuring comprehensive AI governance throughout the model lifecycle including development, validation, deployment, monitoring, and decommissioning.
• Represents the organization in industry, regulatory, and peer forums related to data governance and AI.
• Designs, implements, and enhances governance frameworks, policies, and standards consistent with DAMA-DMBOK, DCAM, and banking regulations.
• Implements unified data classification and ownership models to ensure accountability, and enforces privacy, security, retention, and quality policies that comply with GDPR, CCPA, and relevant regulations.
• Partners with Information Security for incident response for data breaches, model failures, and AI ethics issues.
• Builds partnerships with leadership, business units, Technology, Risk, Compliance, Legal, HR, and Audit.
• Partners with Risk and Compliance to establish risk assessments for data governance and AI/ML platforms, addressing compliance gaps.
• Supports regulatory examinations, audits, and assessments for data governance and model risk.
• Implements and enforces data quality standards through automated monitoring, remediation, and comprehensive metadata management for lineage, glossaries, and cataloging.
• Collaborates with Data Engineering to embed quality controls in pipelines and analytics.
• Supports data-driven decision making while maintaining governance controls.
• Influences technology architecture and investment decisions impacting data governance.
• Recruits, mentors, and develops a high-performing team of governance, ethics, and compliance professionals.
• Establishes clear roles, responsibilities, and development paths for governance team members.
• Promotes knowledge sharing, best practices, and cross-training across the organization.
• Other duties as assigned.

• Bachelor’s degree in Data Science, Computer Science, Engineering, Information Technology, or a related technical field (Masters/PhD preferred).
• 10+ years of experience in data governance, AI/ML delivery, or risk management.
• 5+ years of experience in a technical leadership role.
• Proven leadership and mentoring of cross-functional teams; excellent communication and stakeholder engagement.
• Expertise in Databricks, Python, cloud data lakes (Delta Lake, Azure, AWS S3); skilled in R, SQL, MLOps tools (MLflow, Kubeflow, Sage Maker, Azure ML).
• Strong experience in AI/ML lifecycle, responsible AI, deploying solutions on Databricks.
• Knowledge of regulatory compliance (PCI, GLBA, GDPR), agile methodologies, Dev Ops, CI/CD, infrastructure-as-code.
• Experience in data visualization (Sigma, Tableau, Power BI, Looker, Qlik).
• Experience with pipeline orchestration (Airflow, Azure Data Factory, AWS Glue).
• Familiar with Scrum, Kanban, SAFe, and product management frameworks.
• Excellent organizational and prioritization skills, with the ability to balance multiple issues and projects in a fast-paced environment.
• Excellent verbal, written, and interpersonal communication skills.
• Must be self-motivated with strong initiative, high level of accountability, and attention to detail.
• Must be a self-starter with the ability to work independently and as part of a team.
• Ability to always maintain a high degree of ethical standards and complete confidentiality.

• Financial services, digital banking transformation or Fintech experience.
• Working in the Data, Enterprise Architecture, or Risk Management Office.
• Digital assets, blockchain, cryptocurrency, DeFi governance expertise.
• Strong grasp of banking products, operations, and value chains.
• Advanced Databricks, Python, SQL, and cloud data engineering proficiency.
• Experience…