SVP, Data Governance & AI Responsibility

About the Role

The SVP, Data Governance & AI Responsibility leader will establish and lead enterprise governance for data and AI, ensuring compliance, quality, and responsible innovation across strategic platforms and domains.

Key Responsibilities

• Data governance tools: Catalog, Quality, Lineage, Recon, Retention
• External domain enablement: Risk, Ops, Finance
• Legacy data documentation and retention risk management
• DataOps and QE testing for strategic migrations
• Regulatory compliance: Reg SP, CCPA, FINRA, SEC
• AI governance and MLOps frameworks
• Lead change forums: SteerCOs, readouts

Strategic Objectives

• Strengthen core data governance capabilities
• Enable DPO adoption in external domains (Risk, Operations, Finance etc)
• Mitigate legacy data risks during integrations
• Operationalize DataOps and testing
• Ensure regulatory compliance and remediation
• Build AI governance, Lead AI governance forums, Change mgmt and MLOps foundations

Requirements

• A bachelor's or master's degree in business, Computer Science, Information Systems, Data Science, Engineering, or a related field.
• At least 15 or more years of experience in product management, including a proven track record of leading significant successful data transformation initiatives in complex environments.
• Minimum 5 or more years of experience in data platform and services build-out in partnership with engineering teams and data product ownership in a mid to large scale enterprise.
• Proven experience in a senior leadership role over enterprise Data governance initiatives: Catalog, Quality, Lineage, Recon, and Retention.
• Experience leading teams through significant transformations, particularly in migrating from legacy systems to modern cloud architectures.
• Exceptional communication and stakeholder management skills.
• Demonstrated ability to foster a collaborative and innovative team culture.
• Experience with DataZone from AWS a plus.