Director, Operations IT – Data Lead

ABOUT ASTRAZENECA AstraZeneca is a global, innovation-driven BioPharmaceutical business dedicated to the discovery, development, and commercialization of prescription medicines for serious diseases. We are not just one of the world's leading pharmaceutical companies; we strive to create a Great Place to Work, fostering an inclusive culture that values diversity and collaboration. Committed to lifelong learning and growth, AstraZeneca provides an environment where individuals can push the boundaries of science and make a significant impact on medicine, patients, and society. ABOUT THE ROLE This is a strategic technology leadership role responsible for shaping the Operations IT data, semantic and knowledge strategy. Working across Enterprise IT, the Operations Data Office and business domains, the role will drive the technical governance, integration and standardisation of data across Operations, while evolving data products, semantic capabilities and enterprise knowledge. This will create trusted, reusable foundations that accelerate Digital & AI, improve decision-making and drive operational value. Data, Semantic & Knowledge Strategy Own and deliver the Operations IT strategy and roadmap for data, semantic and knowledge technologies, aligned with Enterprise IT, Enterprise Architecture, the Operations Data Office and business priorities. Define the technology evolution from data products → data contracts → semantic layers & knowledge graphs, creating trusted and reusable foundations for analytics, AI and automation. Drive alignment and integration of data capabilities across Operations domains, enabling consistent standards, interoperability and reuse. Partner with business teams and the Operations Data Office to translate business standards, governance and semantic requirements into scalable technology capabilities. Identify opportunities to use data, semantics, knowledge and AI to improve operational performance, decision-making and business outcomes. Data Products & Semantic Layer Support the delivery and lifecycle management of enterprise data products across Manufacturing, Supply Chain, Quality, Procurement, Sustainability and wider Operations. Establish scalable capabilities for data product management, including cataloguing, discoverability, quality monitoring, lineage, access, documentation and lifecycle management. Build and evolve the semantic layer, operationalising business-defined entities, metrics, relationships, hierarchies, definitions and rules into reusable technology assets. Drive the evolution toward semantic data products that enable consistent business meaning and interoperability across domains, analytics, applications, automation and AI. Monitor adoption, reuse, quality and business value through defined KPIs. Implement business strategy for AI-ready data products. Knowledge & Unstructured Data Lead the technology strategy and delivery of knowledge graphs and enterprise knowledge capabilities, connecting structured and unstructured information across Operations. Implement semantic models, ontologies, taxonomies, metadata and relationship models in partnership with business owners and the Operations Data Office. Improve the management, integration and discoverability of unstructured information, including documents, procedures, specifications, technical content and quality records. Partner with Digital & AI teams to make enterprise data and knowledge accessible to GenAI, search, agents, recommendations and intelligent automation. Leverage AI and automation to classify, enrich, connect and extract value from enterprise information at scale. Governance, Integration & Business Partnership Partner with the Operations Data Office and business data owners to operationalise data governance, semantic standards, data contracts and information management requirements across the technology landscape. Enable the integration and interoperability of data across Operations domains, ensuring common standards and approaches are consistently implemented. Ensure technology platforms support appropriate data quality, metadata, lineage, security, access control, retention, compliance and auditability. Maintain clear accountability between business ownership of data meaning, quality and standards and IT ownership of the technology capabilities that enable them. Drive alignment across business domains, Enterprise Architecture, Engineering and Digital & AI to maximise consistency, integration and reuse. Act as a trusted technology partner to senior business and data leadership on the evolution of Operations data and knowledge capabilities. Leadership & Stakeholder Management Build strong partnerships across Operations, the Operations Data Office, Enterprise IT, Enterprise Architecture, Cyber Security, Digital & AI and Engineering. Influence senior stakeholders and drive alignment across complex business and technology organisations. Develop the capabilities, talent and operating models required to support the evolving data, semantic and knowledge landscape. Foster a culture of reuse, interoperability, data-driven decision-making, knowledge sharing and continuous improvement. Required qualifications: Bachelor's degree in Information Technology, Computer Science, Engineering, Data Management, a related field, or another research-intensive discipline; equivalent professional experience will also be considered. Significant experience leading data, information management, digital transformation, or technology delivery initiatives — evidenced by the scope, complexity and business impact of what was owned. Proven experience developing and executing data strategies and delivering business-critical data products, information management capabilities, or knowledge products. Strong understanding of modern data architectures, cloud data platforms, semantic layers, metadata management, data contracts, and information management technologies. Hands-on experience delivering GenAI products in a live business environment and taking them through the software development lifecycle, whether in a data or product capacity. Demonstrated ability to translate business-defined concepts, KPIs, process rules, and domain standards into reusable data product capabilities and progressively governed semantic layer implementations. Demonstrated experience leading multiple cross-functional delivery pods across multiple business domains — through direct people leadership, matrixed/virtual team leadership, or embedded consulting delivery roles. Strong stakeholder management and executive communication skills with the ability to influence across business, data governance, and technology organizations. Experience operating within a federated data governance model involving business data owners, data stewards, enterprise governance teams, and technology delivery teams. Preferred qualifications: Experience implementing semantic layers, semantic products, data contracts, Knowledge Graphs, ontologies, taxonomies, or knowledge management platforms, including piloting these capabilities in partnership with cloud data platform vendors and systems integrators. Experience defining semantic certification processes or governed data product adoption frameworks. Familiarity with AI, Generative AI, Retrieval-Augmented Generation (RAG), agentic workflows, and knowledge-centric AI architectures. Experience within Supply Chain