Data Engineering Lead

You’ll Influence TheLives OfMillions Globally

Do you want to be part of one of the global 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 DevelopmentData Platformteam here at AZ plays a key role introducing process and technology improvements such as Data Mesh, Agile, DevOpsand the very latestengineering tools to maximise velocity and business value.

Apply Your Expertise InADynamic Team

You will join the Drug Discovery Data Platform leadership team, delivering data and digital capabilities across Target Identification and discovery through design, make, testand analyse.

This is a hands-on technical leadership role. You will lead multidisciplinary teams delivering trusted data products, analytical productsand AI-enabled solutions across the full lifecycle-from discovery and architecture through engineering, deployment, adoption, monitoringand continuous improvement.

Your work will include:

• Building discoverable, interoperableand trusted data products for scientific and business users.

• Developing AI solutions such as predictive analytics, intelligent search, knowledge assistants, RAG, agentic workflowsand automation.

• Setting standards for data engineering, APIs, analytics, machine learningand generative AI.

• Providing hands-on technical leadership through architecture, design reviews, prototypes, code contributions, performance optimisationand production support.

• Improving delivery through Agile, DevOps, DataOps, MLOpsand LLMOpspractices, automationand self-service capabilities.

• Working with product managers, architects, data owners, scientistsand 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 technologiesare essential.

Key Responsibilities

Technical Leadership and Architecture

• Define technical direction for data products, analytics platformsand AI-enabled capabilities.

• Design secure, scalable, resilientand cost-effective architectures for batch, streaming, event-driven, API and AI workloads.

• Establish reusable patterns for data contracts, domain-owned data products, semantic models, metadata, lineageand self-service.

• Lead decisions across cloud infrastructure, data storage, processing, orchestration, integration, AI servicesand application development.

• Manage technical debt, platform risks, performance, dependenciesand cloud costs.

• Ensure solutions meet relevant standards for security, privacy, compliance, validation, resilience, auditabilityand responsible AI.

Hands-on Engineering

• Contribute to production-quality code, prototypesand technical investigations, primarily using Python and SQL.

• Build and review data pipelines, transformation frameworks, APIs, analytical productsand AI application components.

• Develop cloud-native solutions using containers, serverless services, managed platforms, event-driven architecturesand infrastructure as code.

• Establish practices for Git-based development, automated testing, CI/CD, release management, observabilityand operational support.

• Apply data quality checks, monitoring, performance testingand secure software supply-chain practices.

• Support incident investigation, root-cause analysisand continuous improvement.

AI and Advanced Analytics

• Identifyvaluable and feasibleapplications of AI and advanced analytics in drug discovery.

• Engineer production AI solutions covering data preparation, model or foundation-model integration, retrieval, tool use, evaluation, deployment, monitoringand cost management.

• Move suitable concepts from experimentation into reliableservices.

Product and Delivery Leadership

• Translate user and business needs into product outcomes, technical options, delivery plansand success measures.

• Balance speed with quality, maintainability, security, compliance, resilienceand total cost of ownership.

• Lead delivery across globally distributed teams, including the UK, Chennai, Barcelonaand Guadalajara.

• Maintain clear technical designs, data definitions, data contracts, AI documentation, runbooks, support modelsand ownership.

• Promote reuse, interoperability and continuous feedback across products and domains.

What You’llBring

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, softwareor AI products in the cloud.

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

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

• Experience with AWS, Azureor comparable cloud platforms, including CI/CD, infrastructure as code, containersand production operations.

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

• The ability to make pragmatic architectural decisions and communicate complex technical topics clearly.

• 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 Enterpriseand container platforms. Equivalent technologies are equally relevant.

We are particularly interested in experience with:

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

• Software engineering: Python, APIs, microservices, containers, serverless architectures, automated testingand secure development.

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

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

• AI engineering: LLM APIs, vector or hybrid search, RAG, prompt and model management, tool integration, evaluationand monitoring.

• Analytics and visualisation: Power BI or equivalent tools and scalable, user-centred insight products.

• Engineering operations: Service ownership, incident management, reliability engineeringand operational readiness.

Experience with third normal form, dimensional modelling and star schemas is useful, alongside the judgement to select the right modelling approach for each use case.

Desirable Experience

• Experience in pharmaceutical, biotechnology, healthcare, clinical researchor another regulated industry.

• Understanding of drug discovery or scientific data, including Target Identification, design, make, test and analyse.

• Experience establishingengineering standards, reference architectures, reusable platformsor internal developer platforms.

• Experience with FinOps, platform scalability and sustainable technology delivery.

• 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 graphsor graph-based search.

• Experience with human-in-the-loop decision support or workflow automation.

• A degree or equivalent experience in computer science, engineering, data scienceor a related discipline.

WHY JOIN US?

We’rea network of entrepreneurial self-starters who contribute to something far bigger. There’sa diversity of expertisein our Technology group that’sunique 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. We optimise and evolutioniseAstraZeneca by maximising efficiencies and finding new ways to drive productivity. From automation to data simplification.

A place to be open and transparent - we speak up, think creatively and share ideas. Our diverse contributions help us to make better decisions. But we have a constant drive to innovate, and an appreciation for high standards. 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.

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. Join us in our unique and ambitious world.

Date Posted

Closing Date

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.