Technical Lead Data Engineer

Job Title: Technical Lead Data Engineer

Global Career Level: E

About our Team:

AstraZeneca is transforming into an AI- and data-led enterprise. Within R&D the Predictive AI & Data team turns complex information into practical life-changing insights that improve patient outcomes. We invent build and deliver novel solutions alongside leading experts leveraging cutting-edge techniques in data AI and machine learning. We work inclusively across diverse disciplines and partners aligning to business needs and delivering measurable value.

Introduction to role:

We are seeking a hands-on Technical Lead Data Engineer to lead data architecture modeling warehousing transformation and platform engineering that accelerates scientific decision-making across Clinical Pharmacology & Safety Science (CPSS). You will design and deliver scalable FAIR-aligned data solutions on enterprise infrastructure driving positive disruptive transformation toward AstraZenecas Bold Ambition for 2030. This role partners closely with R&D IT and DS&AI and collaborates globally with colleagues in Sweden the United Kingdom and the United States.

Accountabilities:

• Data platform architecture: Design implement and operate robust secure and scalable data platforms and services that enable discovery access and reuse (FAIR) with clear SLOs for reliability and performance.

• Modeling and warehousing: Define canonical data models dimensional schemas and lakehouse/warehouse layers; implement semantic modeling; optimize storage compute and query performance.

• Data integration: Build and harden ingestion frameworks for structured and unstructured data; standardize metadata lineage and cataloging; ensure interoperability across domains.

• Governance and quality: Establish and enforce standards for data quality access control retention and compliance; implement monitoring observability and automated data quality checks.

• Infrastructure engineering: Operate solutions across Unix/Linux HPC and cloud (AWS preferred) leveraging infrastructure-as-code to ensure reliability scalability and cost efficiency.

• Collaboration: Translate scientific and business requirements into well-architected designs; co-create solutions with CPSS stakeholders R&D IT and DS&AI; set technical direction and roadmap.

• Engineering excellence: Apply software engineering best practices (version control CI/CD automated testing design patterns code review) to deliver maintainable resilient systems.

• Enablement: Produce high-quality documentation reusable components and guidance; mentor engineers and uplift data engineering practices across teams.

Essential Skills/Experience:

• Education: Degree in Computer Science Engineering or related field or equivalent industry experience.

• Experience:1015 years of relevantexpertiseas an individual contributor with extensive hands-on involvement.

• Programming: Strong Python expertise; familiarity with Java or C; ability to write clean testable performant code.

• Platform architecture: Proven experience architecting and building data platforms and data-driven solutions at scale.

• Software engineering: Track record delivering production-grade systems in data AI or scientific domains; proficiency with Git CI/CD automated testing design patterns and DevOps/SRE practices.

• Data modeling and warehousing: Experience with dimensional modeling semantic layers and warehouse/lakehouse technologies (e.g. Snowflake Databricks TileDB).

• Databases: Hands-on experience with SQL and NoSQL systems query optimization and performance tuning.

• Compute environments: Practical experience with Unix/Linux HPC and cloud platforms (AWS preferred) including infrastructure-as-code (e.g. Terraform/CloudFormation).

• Translation of needs: Ability to convert scientific/business requirements into robust technical solutions with measurable outcomes.

• Technical leadership: Demonstrated experience leading end-to-end delivery setting engineering standards and guiding teams while remaining hands-on.

• Core skills: Excellent problem-solving analytical and critical-thinking capabilities; attention to detail; strong communication and stakeholder management skills.

Desirable Skills/Experience:

• Generative and agentic AI: Experience developing LLM-enabled data services MCP servers and agentic workflows.

• Data processing and integration: Experience processing integrating structured and unstructured data at scale; familiarity with streaming and batch patterns.

• Life sciences: Experience with clinical or pre-clinical drug discovery imaging and bioinformatics data; understanding of domain ontologies and scientific data standards.

• Governance and compliance: Experience with data governance privacy security-by-design and relevant regulatory frameworks.

When we put unexpected teams in the same room we unleash bold thinking with the power to inspire life-changing -person working gives us the platform we need to connect work at pace and challenge perceptions. Thats why we work on average a minimum of three days per week from the office. But that doesnt mean were not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Why AstraZeneca:

We follow the science to explore and innovate fusing data and technology with the latest scientific advances to achieve the next wave of breakthroughs. We listen and learn from people living with the diseases we treat to better understand needs and design the right interventions. If your passion is science and impact on patients lives this is the place to build a career that matters.

Ready to make an impact Apply now and join us in shaping the future of data architecture and infrastructure at AstraZeneca.

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.