You’ll Influence The Lives Of Millions Globally Do you want to be part of one of the general leading innovators in the biopharmaceutical business in shaping the technology that reinforces everything we do that helps AstraZeneca push the boundaries and turns ideas into life changing medicines?

The Drug Development Data

Platform team here at AZ plays a key role introducing process and technology improvements such as Data Mesh, Agile, DevOps and the very latest engineering tools to maximise velocity and business value.

Apply Your Expertise In A Dynamic Team You will join the Drug Discovery Data Platform leadership team, delivering data and digital capabilities across Target Identification and discovery through design, make, test and analyse. You will lead multidisciplinary teams delivering trusted data products, analytical products and AI-enabled solutions across the full lifecycle—from discovery and architecture through engineering, deployment, adoption, monitoring and continuous improvement. Building discoverable, interoperable and trusted data products for scientific and business users.

Setting standards for data engineering, APIs, analytics, machine learning and generative AI. Providing hands-on technical leadership through architecture, design reviews, prototypes, code contributions, performance optimisation and production support. Improving delivery through Agile, DevOps, DataOps, MLOps and LLMOps practices, automation and self-service capabilities.

Working with product managers, architects, data owners, scientists and stakeholders to prioritise opportunities and deliver measurable outcomes. Coaching senior engineers and technical leads and promoting responsible, well-governed use of AI. You will primarily work with our AWS data and analytics ecosystem, while collaborating with teams using Azure.

Strong engineering judgement and experience selecting appropriate technologies are essential.

Key Responsibilities Technical Leadership and Architecture Define technical direction for data products, analytics platforms and AI-enabled capabilities. Establish reusable patterns for data contracts, domain-owned data products, semantic models, metadata, lineage and self-service. Lead decisions across cloud infrastructure, data storage, processing, orchestration, integration, AI services and application development.

Manage technical debt, platform risks, performance, dependencies and cloud costs. Hands-on Engineering Contribute to production-quality code, prototypes and technical investigations,



primarily using Python and SQL. Build and review data pipelines, transformation frameworks, APIs, analytical products and AI application components.

Develop cloud-native solutions using containers, serverless services, managed platforms, event-driven architectures and infrastructure as code. Establish practices for Git-based development, automated testing, CI/CD, release management, observability and operational support. Apply data quality checks, monitoring, performance testing and secure software supply-chain practices.

Support incident investigation, root-cause analysis and continuous improvement. Engineer production AI solutions covering data preparation, model or foundation-model integration, retrieval, tool use, evaluation, deployment, monitoring and cost management. Balance speed with quality, maintainability, security, compliance, resilience and total cost of ownership.

Maintain clear technical designs, data definitions, data contracts, AI documentation, runbooks, support models and ownership. What You’ll Bring Essential Experience Experience as a Data Engineering Lead, Software Engineering Lead, Platform Engineering Lead, AI Engineering Lead or equivalent. A strong hands-on background building and operating production data, software or AI products in the cloud.

Strong programming and engineering capability in Python and SQL, including testing, code review, debugging, optimisation and production support.

Experience with data modelling, batch and streaming pipelines, orchestration, data quality, metadata, lineage, data contracts and observability.

Experience with AWS, Azure or comparable cloud platforms, including CI/CD, infrastructure as code, containers and production operations.

Experience partnering with product, architecture, security, governance, data science and business teams to deliver measurable outcomes.

Experience coaching engineers and raising engineering standards.

Relevant Technical Experience

Our environment includes AWS and Azure services, S3, Redshift, Athena, Aurora, PostgreSQL, Snowflake, Starburst, Glue, Lambda, EMR, Spark, dbt, Power BI,



GitHub Enterprise and container platforms.

Data platforms and processing: Lakehouse or warehouse architectures, Spark, SQL transformation, streaming and workflow orchestration.

Software engineering: Python, APIs, microservices, containers, serverless architectures, automated testing and secure development.

Cloud and platform engineering: Terraform or equivalent, CI/CD, secrets management, observability, resilience, automation and cloud cost optimisation.

Data product engineering: Data contracts, semantic layers, metadata, lineage, catalogues, discoverability, interoperability and self-service.

AI engineering: LLM APIs, vector or hybrid search, RAG, prompt and model management, tool integration, evaluation and monitoring. Power BI or equivalent tools and scalable, user-centred insight products.

Engineering operations: Service ownership, incident management, reliability engineering and operational readiness. Understanding of drug discovery or scientific data, including Target Identification, design, make, test and analyse.

Experience establishing engineering standards, reference architectures, reusable platforms or internal developer platforms.

Experience taking AI or machine learning solutions from experimentation into supported production services.

Experience with data mesh or domain-oriented data products, event-driven architectures, real-time data products, knowledge graphs or graph-based search. A degree or equivalent experience in computer science, engineering, data science or a related discipline. We’re a network of entrepreneurial self-starters who contribute to something far bigger.

There’s a diversity of expertise in our Technology group that’s unique to AstraZeneca - it allows us to dive deep into exploring new leading-edge technology. We enable AstraZeneca to perform at its peak by delivering world-class technology and data solutions, unlocking the potential of science. From automation to data simplification.

It takes challenging the status quo to add value in our ever-evolving environment. We love it here because put simply, we make a meaningful impact. That's why we work, on average, a minimum of three days per week from the office.

We balance the expectation of being in the office while respecting individual flexibility. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.

SummaryLocation: Spain - BarcelonaType: Full time

📌 Lead Data Engineer / Team Lead (Barcelona)
🏢 AstraZeneca
📍 Barcelona