We are the people who give possibilities purpose

BD is one of the largest global medical technology companies in the world. Advancing the world of health™ is our Purpose, and it’s no small feat. It takes the imagination and passion of all of us—from design and engineering to the manufacturing and marketing of our billions of MedTech products per year—to look at the impossible and find transformative solutions that turn dreams into possibilities.

Job Description

Enterprise Data Architecture and Strategy

• 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.

Master Data Strategy, Architecture & Governance

• 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.

Data Analytics Governance & Data Domain Ownership

• 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.

Data Platforms Governance

• Provide strategic leadership and accountability for data platforms, data engineering, and analytics delivery, with a strong focus on Databricks lakehouse architecture.

• Oversee the governan