VP, Data Strategy & Governance

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The Vice President, Data Strategy & Governance is a senior executive accountable for defining, advancing, and operationalizing the enterprise data strategy. This leader drives the full lifecycle of data governance — from policy design and sensitive data management to technology enablement, data quality, and regulatory compliance. Serving as a strategic advisor to executive stakeholders across all business units and technology functions, the VP partners closely with Cybersecurity,Enterprise Architecture, and line-of-business leaders cultivate a data-rich, AI-ready environment grounded in trust, quality, and accountability.

The VP is a visionary organizational builder who attracts and develops world-class talent, shapes data culture, and influences enterprise-wide change. This individual would need to partner across business and technology leaders to drive a product mindset and promote adoption to realize business outcomes. This leader will promote a data product operating model by embedding accountability for data quality, metadata, lineage, access, and data lifecycle management across the enterprise.

This leader brings deep command of applied data governance practices, data protection strategies, emerging ML/AI-based governance tools, and the legislative landscape governing personal and sensitive data. Their work directly enables the organization's digital and analytics ambitions while fortifying its cyber-breach resistance posture.

Key Responsibilities Strategic Initiatives & Program Outcomes Establish and own the enterprise data strategy, translating organizational goals into a continuously evolving roadmap of data capabilities spanning people, process, technology, and budget.

Lead portfolio governance of enterprise data programs, ensuring initiatives are prioritized, resourced, and delivering measurable business outcomes aligned to financial and strategic objectives.

Partner with the Chief Data & Analytics Officer and executive peers to articulate the value of data assets, influence investment decisions, and embed data thinking into enterprise planning cycles.

Drive enterprise-scale data science and AI readiness by ensuring foundational data infrastructure, lineage, quality, and accessibility meet the demands of advanced analytics and generative AI use cases.

Develop and maintain a data product mindset across the organization — enabling reusable, trusted, and well-documented data assets that accelerate time-to-insight across business units.

Team Building & Organizational Development Build, lead, and continuously develop a high-performing, world-class team of experts spanning sensitive data governance, data lineage and mapping, data enrichment, data quality, data democratization, and program management.

Foster a culture of accountability, innovation, and continuous learning; champion data literacy initiatives that upskill the broader organization and democratize access to trusted data.

Act as a Culture Shaper and Talent Builder — recruiting diverse, senior talent, establishing clear career pathways, and mentoring future data leaders across the enterprise.

Operate as a cross-functional influencer and collaborator, building strong relationships across Technology, Cybersecurity, Legal, Compliance, Finance, and business unit stakeholders to drive data governance adoption ine team operating models, performance metrics, and OKRs that demonstrate the strategic and financial impact of the data governance function.

Technology Implementations & Tools Lead evaluation, selection, and implementation of enterprise data governance platforms, data catalog and marketplace solutions, data quality tooling, and metadata management systems.

Modernize data scanning, automated tagging, and labeling capabilities to improve governance efficiency, enable proactive data classification, and strengthen data loss prevention (DLP) outcomes.

Partner with Security Architecture and Enterprise Architecture to design and deploy solutions that deliver integrated data governance and data security at scale — on-premises and across cloud environments.

Invest in and operationalize innovative ML/AI-based approaches for data governance, including automated lineage discovery, anomaly detection, synthetic data generation, and differential privacy techniques.

Maintain awareness of the evolving data governance technology landscape; drive a buy/build/partner strategy that balances innovation with cost discipline and commercial…