Director, AI-Ready Data Preparation

This role leads the enterprise capability that prepares, processes, and provisions AI-ready data at scale, using approved standards, tooling, and guidelines. The team builds and operates next generation data preparation, integration, orchestration, transfer, and obfuscation capabilities, driving increasing automation and self service for data consumers. The Senior Director also delivers and owns priority enterprise data products, demonstrating how to apply enterprise patterns end to end to accelerate time to insight for AI/ML and analytics through compliant, reliable, and efficient pipelines. Ready to develop how AI-ready data is composed and consumed across a global organisation? Accountabilities Lead the strategy and execution for AI-ready data preparation across high priority AI use cases, shifting from custom solutions to reusable, self-serviceable data products with growing automation. Build, own, and operate high value enterprise data products for AI/ML and analytics, applying enterprise schemas, lineage models, SLAs/SLOs, data contracts, and quality rules that drive trust and adoption. Implement DataOps practices and AI-driven automation that streamline ingestion, transformation, testing, and deployment, while enabling self-serve discovery, access, and provisioning on approved enterprise platforms. Design and run robust end-to-end data pipelines (ingest/store * prepare * provision) with scalable orchestration, metadata-driven processing, performance tuning, and cost optimisation on sanctioned cloud platforms. Apply enterprise security controls and approved obfuscation patterns such as masking, tokenisation, and anonymisation to enable safe AI experimentation and compliant data transfer at scale. Build and maintain exemplar implementations and reusable components that showcase approved ways of working for data storage, preparation, provisioning, integration, orchestration, transfer, and obfuscation. Lead and grow high performing engineering teams across onshore and offshore locations, manage suppliers effectively, and ensure on time, high quality delivery using enterprise tooling and delivery frameworks. Evaluate and pilot emerging capabilities within enterprise guardrails, make clear buy versus configure recommendations, and generate evidence of value and adoption to scale successful patterns. How will you push the boundaries of what AI-ready data can do here?

• Extensive data engineering leadership with a track record delivering production grade data products and platforms supporting AI/ML and analytics.
• Data product and DataOps expertise: Hands on proficiency with data product contracts, lineage, quality SLAs, CI/CD for data, automated testing, and metadata driven pipelines that enable self service.
• Integration, orchestration, and storage: Deep experience with batch/streaming integration, workflow orchestration, and scalable storage/processing on modern cloud data platforms, including performance and cost optimisation.
• Security and obfuscation: Practical application of enterprise security controls, secure data transfer, and approved obfuscation techniques in regulated environments.
• Architecture and design patterns: Strong command of applying enterprise data/application design patterns and microservices/event driven approaches using sanctioned tools and reference implementations.
• Able to move at pace and lead and inspire technical team, whilst working within a rapid evolving, often ambiguous business context.
• Innovates, experiments and brings external perspectives, with a track record of applying innovative technologies and approaches to increase speed, quality and compliance if data.
• Partner and vendor management: Ability to influence senior collaborators, manage partner ecosystems, and build high performing teams; clear communication of value, outcomes, and adoption metrics.

Desirable Skills/Experience Experience leading large-scale AI/ML or analytics transformation programmes in sophisticated global organisations. Background in building or operating shared enterprise data platforms or internal data marketplaces. Familiarity with regulated industries such as life sciences, healthcare, or financial services. Proven track record to translate strategic business priorities into actionable roadmaps for AI-ready data capabilities. Track record of nurturing engineering excellence through coaching, standards, and communities of practice. When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility.

Senior Director, AI-Ready Data Preparation We're building a connected, end-to-end Enterprise AI engine - uniting data foundations, AI technology, process reinvention, and business-facing AI to accelerate results across the whole value chain. Success depends on being outstanding connectors: you'll actively harness existing capabilities, celebrate and promote reuse, export breakthrough ideas across geographies and functions, and obsess over scaling impact rather than building in isolation. If you thrive in high-collaboration environments where your role is to turn sophisticated, cross-functional problems into reusable, enterprise-wide capabilities - and where the measure of success is adoption and scale, not just innovation - you'll have the platform (and sponsorship) to make it real. Introduction to role, AstraZeneca offers an environment where innovation in digital, data and AI directly connects to transforming patient outcomes worldwide. Curiosity is encouraged, diverse perspectives are welcomed, and teams collaborate across subject areas to solve sophisticated scientific and technical challenges with real urgency. With strong investment in technology, learning and development, alongside a culture that values experimentation and smart risk-taking, this is a place to shape the future of healthcare while building a long-term career with impact.