Senior Director, Enterprise Data Strategy & Governance

We Are The People Who Give Possibilities Purpose

• Define and execute the enterprise data strategy aligned with digital transformation, AI/ML enablement, and business priorities.
• Provide technical oversight for Databricks architecture and design standards, driving governance, performance optimization, and best practices across the data ecosystem.
• Drive standardization and simplification of data across ERP, CRM, supply chain, and analytics platforms.
• Define enterprise data models and interoperability standards across structured and unstructured data domains.
• Enable scalable, reusable, and governed data products to support advanced analytics and AI use cases.

• Define and lead the global Master Data Management (MDM) strategy across key domains:
  Product, Customer, Vendor/Supplier, Finance, and Location.
• Establish and drive clear business ownership of master data by identifying and formalizing domain-level data owners aligned to core business processes.
• Partner closely with Integrated Supply Chain, Global Commercial Operations, and Finance teams to embed master data ownership into end-to-end business process accountability.
• Define and standardize master data creation, maintenance, and governance processes aligned to enterprise process models (e.g., Quote to Cash, Source to Pay and Finance).
• Architect and govern MDM platforms and ecosystems, including deep expertise in:
• Reltio (cloud-native, multi‑domain MDM, event‑driven integration)
• SAP MDG (SAP aligned governance, workflow‑driven master data control)
• Establish master data architectural patterns including registry, coexistence, consolidation, and centralized models.
• Define golden record strategy, survivorship rules, matching/merging algorithms, and hierarchy management.
• Implement field‑level governance, including attribute‑level ownership, validation rules, reference data alignment, and lifecycle controls.
• Drive modern MDM capabilities including real‑time/event‑driven MDM, API‑first data services, graph‑based relationships, and AI‑assisted data stewardship.
• Ensure tight integration of MDM with upstream and downstream systems (ERP, CRM, supply chain platforms, and Databricks).
• Manage Product Information Management (PIM) team and define clear ownership for Product master data, ensuring alignment between Product master data, product content, and PIM processes.
• Partner with Regulatory and Quality teams to define standards and governance for PIM systems, ensuring that product attributes, labeling data, and regulatory‑critical fields are accurate, controlled, and compliant across markets.
• Establish master data standards, policies, and controls to ensure consistency, quality, and compliance across all regions and business units.
• Incorporate modern enterprise MDM trends, including AI‑assisted data matching and cleansing, smart suggestions for data stewards, and more automated workflows that reduce manual effort while improving master data quality.

• Own the enterprise data governance framework, including policies, standards, controls, and decision rights.
• Lead Databricks domain‑based governance models with clear accountability for data owners, stewards, and custodians.
• Establish governance for data products, including certification, quality SLAs, lineage, and lifecycle management.
• Implement metadata‑driven governance leveraging tools such as Collibra and/or Alation.
• Enforce data quality management practices including profiling, monitoring, issue remediation, and continuous improvement.
• Partner with Security and Privacy teams to embed data protection, access control (e.g., Immuta), and regulatory compliance.

• Provide strategic leadership and accountability for data platforms, data engineering, and analytics delivery, with a strong focus on Databricks lakehouse architecture.
• Oversee the governance, execution, and delivery of data engineering and analytics solutions, ensuring alignment with enterprise data strategy and governance standards.
• Lead the design and delivery of master data–driven data products across key domains,…