Senior Data Engineer - Data Pipelines

Job Title: Senior Data Engineer - Data Pipelines

Global Career Level: D2

About our Team:

AstraZeneca is transforming into an AI- and data-led enterprise. Within R&D, our Predictive AI & Data team connects expertise across functions to turn 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, pooling knowledge to decode business needs, and applying our technical knowledge to deliver value.

Introduction to role:
We are seeking a Senior Data Engineer focused on building robust scientific data pipelines that accelerate scientific decision-making across Clinical Pharmacology & Safety Science (CPSS). You will design and deliver scalable, production-quality data solutions on enterprise infrastructure, driving positive disruptive transformation aligned to AstraZeneca’s 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:

• Pipeline engineering: Design, implement, and operate fit-for-purpose data pipelines for bioinformatics and scientific data, from ingestion to consumption.

• Workflow orchestration: Build reproducible pipelines using frameworks such as Nextflow (preferred) or Snakemake; integrate with schedulers and HPC/cloud resources.

• Data platforms: Develop data models, warehousing layers, and metadata/lineage; ensure data quality, reliability, and governance.

• Scalability and performance: Optimize pipelines for throughput and cost across Unix/Linux HPC and cloud environments (AWS preferred); implement observability and reliability practices.

• Collaboration: Translate scientific and business requirements into technical designs; partner with CPSS stakeholders, R&D IT, and DS&AI to co-create solutions.

• Engineering excellence: Establish and maintain version control, CI/CD, automated testing, code review, and design patterns to ensure maintainability and compliance.

• Enablement: Produce documentation and reusable components; mentor peers and promote best practices in data engineering and scientific computing.

Essential Skills/Experience:

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

• Minimum 8+ years of relevant experience.

• Programming: Strong Python skills; familiarity with R, Java, or C++.

• Workflow frameworks: Experience building pipelines with Nextflow (preferred), Snakemake, or similar.

• Software engineering: Proven delivery of scalable, production-quality solutions in data, AI, or scientific domains; proficiency with version control, CI/CD, automated testing, design patterns, and DevOps.

• Data engineering: Experience with data modeling, data warehousing, and pipeline reliability.

• Databases: Experience with both SQL and NoSQL systems.

• Compute environments: Hands-on experience with Unix/Linux HPC systems and cloud platforms (AWS preferred).

• Translation of needs: Demonstrated ability to convert scientific/business requirements into robust technical solutions.

• Core skills: Excellent problem-solving, analytical, and critical-thinking skills; attention to detail and strong communication and interpersonal skills.

Desirable Skills/Experience:

• Generative and agentic AI: Exposure to LLM-enabled data workflows or agentic orchestration.

• Bioinformatics: Experience developing bioinformatics pipelines (e.g., NGS, omics, variant calling, QC).

• Architecture: Experience designing data platforms and data-driven solutions (e.g., lakehouse, cataloging, lineage).

• Life sciences: Experience in clinical or pre-clinical drug discovery.

• Data processing methods: Experience developing methods for data parsing, normalization, harmonization, and transformation.

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.

Why AstraZeneca:

This is where data engineering meets pioneering science to tackle complex diseases with courage and curiosity. You will collaborate with diverse experts from industry, academia, and biotechs, using digital, data science, and AI to unlock the next wave of breakthroughs. We value kindness alongside ambition, encourage bold ideas, and support lifelong learning, offering the chance to grow across varied stages and molecules and see your contributions reflected in real-world impact—and, when great science comes alive, recognition through publication.

Call to Action:

Bring your engineering craft to where science and data converge—apply your expertise today to build pipelines that accelerate breakthroughs and improve patient outcomes.

Date Posted

09-Jan-2026

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.

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 authorisation and employment eligibility verification requirements.