Senior Director, R&D Enterprise Data (Architecture/Information)

Join AstraZeneca’s Enterprise Data Office (EDO) as the Senior Director, R&D Enterprise Data (Architecture/Information). In this strategic leadership role, you will define the vision, operating model, and standards for enterprise information architecture across R&D and the wider AstraZeneca enterprise. You will set direction for ontologies, semantic models, and knowledge graphs that enable AI-ready data, FAIR principles, and interoperable data products—powering discovery, development, and delivery. Partnering with R&D IT and business leaders, you will influence investment decisions, establish governance, and drive adoption of data-centric architecture at enterprise scale.

You will collaborate across Heads of IT, Business Partners, Enterprise and Solution Architecture, Data Offices (R&D & EDO), and R&D functions to embed enterprise information architecture into strategy, roadmaps, and value realization.

Accountabilities

• Enterprise information strategy: Define and own the R&D enterprise information architecture strategy, standards, and policies—covering ontologies, semantic modeling, knowledge graphs, metadata, and canonical models—to enable AI-ready, FAIR, and interoperable data.
• Ontology leadership: Set enterprise direction for ontology strategy (domain ontologies, taxonomies, vocabularies), guiding how R&D knowledge is represented and connected across platforms and products.
• Semantic and graph vision: Establish the strategic approach for semantic layers and graph-based knowledge representation, ensuring knowledge graphs underpin analytics, decisioning, and AI/ML use cases.
• FAIR, TRUST and Data Mesh alignment: Champion FAIR/TRUST data and align information architecture with the Data Mesh operating model, defining standards for data products, discoverability, and interoperability.
• Master and reference data governance: Shape and govern master and reference data strategies, ensuring R&D requirements are embedded in enterprise models, stewardship, and quality frameworks.
• Policy, compliance, and risk: Oversee policies for ethical, compliant, and secure data use (including privacy and GxP considerations), integrating information architecture with data governance and risk management.
• Architectural standards and adoption: Set reference architectures and design patterns for data platforms and integrations across hybrid cloud; drive adoption through executive sponsorship, funding models, and accountability.
• Stakeholder influence and value: Partner with senior R&D leaders, across IT and the Data Office, to prioritize investments and measure outcomes, linking information architecture to scientific acceleration, operational excellence, and patient impact.
• Leadership and talent development: Lead and develop a high-performing team of information architecture leaders; foster a culture of strategic thinking, collaboration, and delivery excellence.

Essential skills/experience

• Strategic thought leadership: + 7 years demonstrated success leading enterprise-scale information/data architecture strategy and governance in complex, global organizations.
• Pharma R&D domain knowledge: Experience engaging across R&D lifecycle domains (e.g., discovery, translational science, clinical development, safety, regulatory, real-world evidence) at a strategic level.
• Master/reference data governance: Leadership embedding R&D needs into enterprise master and reference data strategies, stewardship, and operating models.
• Regulatory and governance: Strong understanding of information/data governance frameworks and regulatory environments (e.g., GxP, privacy, data ethics), with experience integrating policy into architecture practice.
• Influence and executive communication: Ability to engage C-suite and senior scientific leaders, set clear direction, secure investment, and demonstrate value through outcomes and metrics.
• Team leadership: Track record building and mentoring senior architecture talent and leading cross-functional teams; skilled in org design and change management.
• Education: Bachelor’s degree (or equivalent experience) in Computer Science, Information Systems, Data Management, or related field.

Desirable skills

• Advanced degree: Post-graduate degree in MIS, Data Management, Knowledge Engineering, or related domain.
• FAIR, TRUST and Data Mesh leadership: Expertise driving adoption of FAIR principles and aligning information architecture with Data Mesh concepts and data product governance.
• Ontology and semantics oversight: Executive-level experience setting direction for ontologies, semantic modeling, and knowledge representation; familia