The Global Lead, Data Architecture & Platforms (internally known as the Director, Data Architecture & Platforms) is responsible for defining and governing the enterprise data architecture, ensuring robust data management, governance, and excellence across the biotechnology value chain. The role ensures that data platforms are designed and operated to deliver trusted, compliant, and high-quality data that fuels analytics, AI, and regulatory reporting. This position leads efforts in data governance, metadata management, master data, and enterprise data modeling, working across business and technology teams to enable a consistent and scalable data ecosystem. 

Key Accountabilities

• Define and maintain the enterprise data architecture, ensuring alignment with business, analytics, and AI strategies
• Lead data and AI governance programs, including policies, stewardship, metadata management, and master data management
• Establish and enforce standards for data quality, lineage, and cataloging across biotech systems and platforms
• Ensure that data platforms (cloud, warehouses, lakes, meshes) are architected for scale, compliance, and interoperability
• Drive adoption of data excellence practices, ensuring consistent definitions, KPIs, and reference data across the organization
• Collaborate with IT, compliance, and cybersecurity to align data platforms with regulatory (GxP, FDA, GDPR) and security requirements
• Provide architectural guidance for new digital and AI initiatives, ensuring data readiness and fit-for-purpose design
• Evaluate and select data management tools, platforms, and vendors to support enterprise data strategy
• Build and maintain a community of practice for data governance and stewardship across functions
• Champion cultural change toward data-driven decision making and literacy across biotech operations
• Manage a team of 2-4 direct reports

Education & Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Management, or related technical field required 
• Master’s degree in Data Architecture, Data Science, or Technology Management preferred
• Certifications in Data Governance (e.g., DGSP, DCAM), Data Architecture (TOGAF, DAMA), or Cloud Data Platforms desirable
• 10+ years of experience in data architecture, data management, or enterprise data governance. 
• At least 6 years in a leadership capacity, guiding teams or governance programs. 
• Strong knowledge of data modeling, master data management, metadata, data cataloging, and governance frameworks. 
• Experience designing architectures in cloud platforms (AWS, Azure) and modern data ecosystems (Snowflake, Collibra, Informatica, Highbyte, Alteryx). 
• Familiarity with regulated biotech or life sciences data environments and compliance standards

Scope & Decision Making

• Accountable for enterprise-wide data architecture and governance standards 
• Ensures data and AI platforms are trustworthy, compliant, and optimized for analytics and AI
• Direct accountability for establishing data quality, governance, and stewardship frameworks
• Collaboration with appropriate teams to influence over enterprise IT architecture and technology roadmap and investments
• Direct impact on the reliability, compliance, and usability of enterprise data for decision making and regulatory filings. 
• Liaises with Quality, Manufacturing, R&D, Supply Chain, and senior business leadership. 
• Provides architectural oversight on data strategy and influences executive-level decisions on digital transformation
• Exercises ownership in defining and enforcing enterprise data standards, governance policies, and architecture principles. 
• Provides independent judgment on platform selection, architecture design, and governance approaches. 
• Responsible for balancing business agility with compliance and standardization

Key Knowledge

• Data Architecture: Expertise in data modeling, enterprise architecture, and cloud-native data platform design. 
• Governance: Strong knowledge of governance frameworks (DAMA, DCAM), metadata management, and master data. 
• Regulatory: Familiarity with biotech regulatory requirements (FDA, EMA, GDPR, GxP) and data privacy laws. 
• Leadership: Ability to drive cross-functional alignment and influence senior stakeholders. 
• Tools & Platforms: Experience with Collibra, Informatica, Alteryx, HighByte, Snowflake, Databricks, or similar data governance/data platform tools. 
• Business: Strong understanding of biotech data domains (manufacturing, quality, supply chain, R&D). 
• Soft Skills: Excellent communication, facilitation, and change management skills. 
• Other: Commitment to building a culture of data excellence and literacy