Senior Manager, Data Governance

Responsibilities

• Owns the enterprise data governance function, designing and standing up the governance framework.
• Defines data domains, data ownership assignments, and stewardship accountability structures across the organization.
• Establishes and publishes data policies covering classification, quality standards, retention, access, and acceptable use.
• Builds a data governance maturity model with measurable milestones.
• Defines enterprise data quality dimensions: completeness, accuracy, timeliness, consistency, uniqueness, and validity.
• Establishes data quality rules and thresholds that the QA function operationalizes in pipeline validation.
• Partners with the Director, Quality Assurance to ensure governance policy translates directly into executable test criteria.
• Affords data lineage and cataloguing capabilities by assessing, selecting, and implementing a data catalogue and lineage tooling.
• Defines metadata standards and ensures data assets are documented, classified, and discoverable.
• Partners with data engineering leaders to ensure pipeline architecture supports lineage capture.
• Serves as the governance anchor for the AI pillar, defining data standards and quality thresholds that apply to AI model inputs.
• Collaborates with technology leadership to ensure governance policy is reflected in AI data sourcing, validation, and monitoring practices.
• Establishes a phased roadmap for AI governance that can expand as the AI program matures, without conflating Data Governance and AI Governance prematurely.
• Builds and operates the data stewardship program; defines steward roles, domain assignments, and operating rhythms.
• Partners with Director, Informatics to embed data definitions and quality standards in acceptance criteria before work enters delivery.
• Partners with Director, Quality Assurance to align governance-defined quality dimensions with QA pipeline validation rules.
• Represents data governance in IT leadership forums and cross-functional executive engagements.

Qualifications

• 7+ years of progressive data management or data governance experience, including at least 2 years owning or leading a governance function.
• Deep familiarity with DAMA-DMBOK and related governance frameworks; ability to translate framework concepts into operational practice.
• Hands-on experience defining data quality dimensions, data ownership models, and data classification schemes in complex data environments.
• Prominent ability to work cross-functionally, building adoption of governance standards through influence rather than top-down mandate.
• Strong communication skills; able to translate governance risk and policy into language meaningful to non-technical executives and business stakeholders.