Associate Director, Data Engineer

About the role

AstraZeneca is looking for an Associate Director, Data Engineer for an in-office role in Barcelona, Spain, with a minimum of three days per week on site; remote or travel flexibility is not available. Working in a small, agile team within the R&D Data Office, you will build reusable data capabilities that make complex R&D workflows simpler, faster and more reliable, and help deliver data aligned to enterprise semantics and standards. You will turn scientific and business requirements into modular, configurable solutions, for example managing multi-omics assay data from planning through to insight.

Key responsibilities

• Prototype, design, develop and deploy modular, configurable data solutions for end-to-end R&D workflows, moving them from prototype to production with lifecycle management and continuous improvement.
• Work within AstraZeneca's architecture, security and operational constraints, applying version control, automated testing, CI/CD, monitoring, observability and documentation.
• Evaluate technical options, plan and track delivery, manage risks and dependencies, and advise on trade-offs across scalability, maintainability, security, cost, performance and reuse.
• Mentor junior colleagues, coordinate delivery across internal contributors and outsourced partners, and troubleshoot issues affecting performance, data flows, metadata integrity and production reliability.
• Build solutions that follow FAIR+T principles, engage on data quality, metadata and governance, and explore safe uses of AI-assisted development, automation and agent-based approaches.
• In the first months, map critical workflows and deliver a high-value prototype; within 6-12 months, standardise and scale reusable capabilities; longer term, help shape enterprise data standards and platforms.

Required profile

• Demonstrated experience designing, developing, deploying and maintaining data and software solutions for complex workflows.
• Ability to design modular, configurable, maintainable and reusable solutions, and to translate business or scientific needs into technical requirements.
• Agile delivery experience, including tracking progress, managing risks and dependencies and reporting to stakeholders.
• Understanding of, or strong interest in, data quality, metadata and FAIR principles.
• Interest in using AI capabilities to improve engineering productivity and data-management workflows.

Required skills

• Strong programming in Python and working knowledge of other languages.
• Cloud experience with AWS or similar (e.g. S3, Lambda, Step Functions, CloudWatch, IAM).
• Relational databases and data integration or processing workflows.
• Desirable: non-relational databases, RDF/OWL/SHACL/SPARQL, data governance, pharmaceutical R&D experience, mentoring and regulated-environment experience.