Job Title: Engineer - Data Engineer

Career Level: C2

Introduction to role:

Are you ready to engineer data products that power faster decisions and accelerate the discovery and delivery of life-changing medicines? As a Data Engineer at AstraZeneca, you will help shape our digital journey by turning complex, diverse data into trusted, reusable products that enable colleagues to move from insight to impact quickly.

You will join a global, agile community that brings together data engineers, product managers, designers and domain guides to solve high-value problems. Using tools such as DBT, Snowflake, FiveTran, Python and AWS, you will build scalable ELT pipelines and modern data products that drive measurable outcomes for teams across the business. How will you apply your craft to cut decision cycles, unlock new analytics and enable the next wave of AI-driven innovation?

Accountabilities:

• Data Product Engineering: Develop, build, and improve scalable ELT pipelines and high-quality data products within a focused Data Mesh approach. Craft trustworthy, reusable datasets for scientists and business teams.

• ELT and Cloud Implementation: Develop robust DBT models, optimize Snowflake performance, and integrate FiveTran connectors; automate orchestration, testing and deployment to deliver reliable and cost-efficient pipelines.

• Data Quality and Observability: Embed data contracts, validation, lineage and monitoring to ensure completeness, accuracy and timeliness; diagnose and resolve production issues proactively.

• Agile Collaboration and Leadership: Work in multi-functional squads, align on standards and ways of working, and chip in to shared patterns, templates and documentation; mentor peers and champion standard methodologies.

• Innovation and GenAI Enablement: Explore and integrate emerging techniques and services, including GenAI patterns, to accelerate analytics, decisioning and automation across use cases.

• Security, Governance and Compliance: Apply security-by-design, access controls and privacy practices; adhere to governance standards while enabling speed and autonomy for domains.

• Value Delivery and Product Attitude: Partner with product owners to prioritize backlogs, measure outcomes and continuously improve; scale solutions from pilot to enterprise adoption to improve impact.

Essential Skills/Experience:

• Architect of Solutions: Lead the design, development, and enhancement of scalable ELT pipelines and Data Products, as part of a Data Mesh inspired strategy.

• Technical Expertise: Demonstrate your expertise in ELT solutions (DBT, Snowflake, FiveTran), Python and AWS ecosystems to deliver exceptional solutions.

• Collaborative Spirit: Work hand-in-hand with global and diverse Agile teams, from data to design, to overcome technical data challenges.

• Innovate & Inspire: Stay ahead of the curve by integrating the latest industry trends and innovations into your work such as GenAI.

Desirable Skills/Experience:

• Hands-on experience implementing Data Mesh concepts (data products, domain ownership, federated standards).

• Advanced Snowflake skills, including performance tuning, scaling, resource optimization and cost management.

• Expertise with dbt Core/Cloud, modular modeling, tests, packages and macros.

• Experience configuring and operating FiveTran (or similar) connectors at scale, including incremental loads and change data capture.

• Orchestration and workflow tools (e.g., Airflow, Dagster, Prefect) and event-driven architectures.

• CI/CD for data (e.g., GitHub Actions, Azure DevOps, GitLab CI), infrastructure as code and automated testing.

• Data modeling (e.g., star schemas, Data Vault), semantic layers and data contracts.

• Data observability and lineage tools; proactive monitoring and incident response.

• Security and governance in AWS (IAM, Secrets Manager, KMS), with privacy-by-design principles.

• Experience enabling analytics, ML and GenAI use cases, including RAG/LLM data pipelines and feature stores.

• Strong communication skills, with the ability to influence standards and coach peers.

• Background in regulated or highly complex data environments is a plus.

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:

Here, data and technology are central to how we accelerate from idea to patient impact. You will work with modern platforms, learn fast through hackathons and experimentation, and see your solutions move from proof of concept to enterprise scale. We pair ambition with support: teams span disciplines and geographies, we encourage curiosity and kindness, and we invest in the tools and time needed to do transformative work. By uniting diverse perspectives to set direction early and build the right solutions, your contributions will help drive smarter decisions and bring vital medicines to people who need them.

Call to Action:

Ready to build data products that shape our digital future and make a measurable difference for patients—join us and make your impact today!

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.