Senior Director, Data Governance and Stewardship

Responsibilities

• Data Governance Strategy & Operating Model
• Evolve and advance Cook Medical’s enterprise data governance framework, operating model, and policy standards.
• Strengthen the Data Governance Councils with cross-functional executive representation; serve as chair or co-chair alongside a senior business sponsor.
• Maintain and advance a data governance roadmap that prioritizes domains based on business impact, maximizing business value, managing regulatory exposure, reducing risk, and enabling AI/agentic use case readiness.
• Define and refine governance policies, standards, and processes covering data ownership, stewardship, quality, classification, definitions, and lifecycle management.
• Business Data Ownership & Stewardship
• Formalize and expand Data Owner assignments across Cook’s critical data domains (e.g., Customer, Product, Supplier, Financial, Regulatory/Clinical, Employee).
• Enable and grow the network of Business Data Stewards embedded within functional areas; refine roles, accountabilities, and operating rhythms to improve engagement and effectiveness.
• Maintain and expand the Business Glossary and enterprise data dictionary, ensuring shared, unambiguous definitions across business units, systems, and geographies.
• Ensure data ownership is embedded in business processes — not just org charts — with owners actively participating in quality remediation, definition management, and governance decisions.
• Data Literacy & Change Management
• Partner with HR, Learning and Talent Development to support a multi-year literacy program building foundational Data/AI fluency across Cook’s business functions, from frontline users to senior leadership.
• Champion the organizational shift from “IT/AI owns data” to “the business owns data, IT/AI enables it.”
• Measure and report governance adoption metrics; identify where additional investment, enablement, or escalation is needed.
• Serve as an internal advocate — positioning data governance as a business enabler, not a compliance burden.
• Master Data Management (Business Process Ownership)
• Partner with IT, data engineering and AI to advance Cook’s MDM program, providing business-side requirements, ownership assignments, and quality standards for master data entities.
• Lead the definition of MDM domains and canonical entities, establishing golden record standards for customer, product, supplier, and related data objects while aligning business stakeholders to governance definitions.
• Oversee the business processes that create, maintain, and retire master data; identify workflow gaps that introduce quality issues and drive process improvement.
• Ensure MDM standards are applied consistently across both traditional enterprise platforms and Palantir Foundry.
• Cross-Platform Data Governance
• Establish and enforce consistent governance standards spanning Cook’s traditional enterprise platforms and Palantir Foundry — ensuring data definitions, quality standards, ownership assignments, and access policies are coherent across environments.
• Serve as the business-side governance authority for Cook’s Palantir Foundry ontology, ensuring objects, properties, and relationships reflect business-owned definitions through a formal review and approval process.
• Partner with IT/AI architecture, data engineering, and the Palantir program team to ensure governance is designed into platform decisions, not retrofitted after the fact.
• Maintain cross-platform data lineage, enabling stakeholders to trace data from source systems through to Palantir Foundry with clear business ownership at each stage.
• Cross-Functional Leadership & Stakeholder Engagement
• Build and maintain trusted relationships with senior leaders across Finance, Commercial, Operations, Supply Chain, R&D, Regulatory, Legal and HR — positioning data governance as a shared business priority.
• Partner with Compliance and Legal to ensure governance policies address applicable regulatory obligations (e.g., MDR, FDA, GDPR, HIPAA) etc.
• Report on governance program health, maturity, and business impact to executive leadership; contribute to the annual data strategy narrative.
• Team & Program Leadership
• Lead and develop a high-impact governance team; define team structure and cultivate team members’ capabilities.
• Provide business requirements when selecting and implementing governance tooling (e.g., data catalog, business glossary, data quality monitoring) in partnership with IT and AI.
• Manage governance program budget and vendor relationships.

  Qualifications

  • Bachelor's degree in Business, Information Systems, Data Management, or a related field; advanced degree preferred.
  • 12+ years of progressive experience in data management, data governance, or a related business function; at least 5 years in a senior leadership role.
  • Certification in data management (CDMP, DCAM) or change management (Prosci, Kotter) highly regarded.
  • Demonstrated success advancing enterprise data governance programs, including operating models, policy frameworks, and stewardship structures.
  • Deep understanding of data governance frameworks (DAMA-DMBOK or equivalent) and how to apply them pragmatically in a complex, global organization.
  • Track record of driving adoption in organizations where data literacy was low and IT historically owned data - comfortable working in a fast-paced agile environment with evidence of measurable cultural change.
  • Strong executive presence and communication skills; able to translate data concepts fluently for non-technical business audiences and influence without direct authority.
  • Proven people-leadership skills; able to translate data concepts fluently for non-technical business audiences and influence without direct authority.
  • Master Data Management (MDM) program leadership experience: defining golden record requirements and managing master data quality with business stakeholders.
  • Experience establishing data quality metrics, monitoring, and remediation processes, and report on data quality and governance health to executive leadership.
  • Experience partnering with IT, data engineering, AI and analytics teams on MDM, data architecture, and data quality programs.
  • Ability to establish consistent governance standards across multiple platforms or data layers, ensuring coherence between integration and intelligence environments.
  • Familiarity with AI/Machine Learning (ML) governance considerations and how data governance intersects with the reliability and trustworthiness of agentic AI workflows.
  • Experience governing data through a major enterprise application transformation (ERP, CRM, or equivalent), including embedding data standards and ownership before go-live.
  • Background in regulated industries — medical devices, life sciences, pharmaceuticals, or manufacturing — where data integrity carries regulatory consequences.
  • Sound knowledge of data privacy, security, and regulatory considerations relevant to a global medical device company (e.g., MDR, FDA, GDPR, HIPAA).
  • Experience in global, multi-entity environments with geographically distributed business units.
  • Experience with data mesh or federated governance models in complex organizations.