Lead AI & Data Engineer - APD Platform

About the role

AstraZeneca's R&D IT organisation is looking for a Lead AI & Data Engineer to join the APD Platform Data & AI team in Barcelona. This senior individual-contributor role provides hands-on technical leadership while supporting the design, development and operation of scalable data and AI capabilities that let R&D teams access, manage, analyse and derive value from trusted data. The APD Platform drives digitisation across synthetic modalities and biologics, covering chemistry, manufacturing and controls.

Key responsibilities

• Design, develop, test, deploy and maintain production-quality data and AI solutions, including pipelines, data products, analytical services, machine learning capabilities and AI applications.
• Collaborate with stakeholders to define technical requirements and deliver scalable, maintainable, observable solutions, and contribute to platform architecture, standards and reusable patterns.
• Prepare, integrate, transform and manage data from structured and unstructured sources, with quality, validation, lineage, metadata, access control and governance.
• Contribute to AI and ML solutions, including model deployment, monitoring, evaluation, versioning and lifecycle management, and possibly large language models, retrieval-augmented generation and AI agents.
• Apply CI/CD, infrastructure as code, containerisation, monitoring, alerting and incident resolution, and support documentation, peer reviews and knowledge sharing.
• Provide technical direction, guide solution design and architecture, mentor engineers and resolve complex technical challenges.

Required profile

• Substantial experience in data engineering, AI engineering, software engineering or a related discipline, with a track record of technical leadership in a complex enterprise environment.
• Strong programming in Python and/or another modern language, with SQL, data modelling, APIs, version control and automated testing.
• Experience designing data pipelines, data products or data platforms with cloud technologies.
• Understanding of MLOps and ML engineering; experience with generative AI, LLMs or AI service deployment is valuable.
• Comfortable with CI/CD, infrastructure as code, containerisation, observability and agile delivery; Spark, Docker, Kubernetes, Terraform or similar is beneficial.
• Ability to explain complex technical ideas to technical and non-technical audiences and to work across multidisciplinary, geographically distributed teams.
• Degree or equivalent professional experience in computer science, engineering, data science, mathematics, life sciences or a related subject preferred.

Required skills

• Python, SQL, data modelling, APIs, version control, automated testing
• Cloud platforms (storage, compute, databases, analytics, ML, identity, monitoring)
• MLOps, CI/CD, infrastructure as code, containerisation, observability
• Desirable: Spark, Docker, Kubernetes, Terraform, Git, PowerBI, Startburst, Snowflake, AWS Glue, LangChain, LangGraph, LangSmith, FastAPI, Pydantic, Pandas
• Desirable: experience in pharmaceutical, biotechnology or healthcare, data governance, privacy, security, FAIR data, knowledge graphs, platform engineering