Data Governance Manager

Quick Facts

• Role: Data Governance Manager (Places organization)

Description

Lead the development of a data governance and data quality foundation across multiple Business Units within the Places organization, enabling the broader AI transformation strategy. You will establish governance and quality standards, operationalize an enterprise-wide data glossary, and implement continuous monitoring and access-control governance. Your leadership will support trusted analytics and AI ingestion for strategic planning and long-term portfolio decisions.

Responsibilities

• Establish and execute a Places-wide data governance and quality strategy across multiple BUs, transforming spatial/location data into trusted analytics-ready assets.

• Define scalable data quality standards at the BU level and partner with engineering and product teams to implement and operationalize a unified enterprise data glossary.

• Create proactive governance systems to monitor data integrity, data quality, and access controls in collaboration with engineering through technical execution.

• Author and implement organizational governance playbooks with clear roles and responsibilities embedded into end-to-end planning, execution, and delivery.

• Partner across BUs, PMO, and Engineering to identify critical data challenges, align on priorities, and manage delivery schedules and risk mitigation.

Requirements

• 10–15+ years of experience in data analytics, enterprise data strategy, and execution.

• 3+ years specialized experience in data governance, data quality frameworks, and AI-readiness transformation.

• Proven record leading complex, cross-functional initiatives in large-scale organizations.

• Hands-on experience guiding Generative AI adoption and establishing enterprise data foundations while enforcing security, compliance, and responsible AI practices.

• Strong program management skills including risk management, prioritization, and orchestration of multiple concurrent workstreams.

• Exceptional communication and stakeholder management ability to translate complex technical data and AI architectures into clear business outcomes.

Benefits

• Opportunity to enable trusted, high-quality insights that power operational excellence and long-term portfolio decisions.

• Meaningful role in building data foundations that support AI ingestion and enterprise analytics at scale.