Senior Data Engineer — Lab Data Pipelines & Data Mesh (12 month FTC) at AstraZeneca

✨ The Stack take on this AstraZeneca job

• 🏢 AstraZeneca has 2 jobs here, 2 with visa sponsorship see all
• 🛂 Visa: Critical Skills Employment Permit. Occupations on the Critical Skills list: €40,904 a year with a relevant degree guide
• 💡 No salary shown. Ask AstraZeneca if it is above the minimum.

Updated 2026-11-05, from our data and official sources.

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About the role

Responsibilities:
- Build resilient lab-to-cloud pipelines: ingest data from instruments, robotics and ELNs into Databricks/AWS with automated validation and provenance.
- Design and publish domain data products into a lakehouse-based data mesh (Delta Lake/Databricks) for self-service analytics and ML.
- Implement ETL/ELT orchestration, retries, lineage, monitoring and runbooks to improve reliability and turnaround times.
- Define standardized schemas and shaping for lab data types (chromatography, spectroscopy, assays, automation outputs).
- Collaborate with scientists, automation and informatics teams to enable LLM/agent-assisted extraction from ELNs and downstream data products.
- Embed security, auditability and role-based access controls to meet regulatory and compliance requirements.
- Provide APIs, curated datasets and documentation so scientists can discover and reuse trusted data without manual copying.

Requirements:
- BS/MS in Computer Science, Data Engineering, Bioinformatics or related discipline.
- 5+ years delivering production-grade data pipelines; life sciences/lab experience strongly preferred.
- Strong Python and SQL skills; experience with Databricks, Delta Lake and pipeline orchestration frameworks.
- Practical knowledge of cloud platforms (AWS services: S3, EC2, EKS, Glue or equivalent) and data mesh concepts.
- Experience with data quality, lineage, monitoring tools and implementing access controls for regulated data.
- Strong collaboration skills: ability to partner with scientists, robotics and IT to translate needs into production solutions.

Responsibilities

Engineer resilient data pipelines to connect laboratory instruments and robotics into a governed data mesh on Databricks and AWS. Develop automated ingestion and validation processes to turn raw lab outputs into trusted, AI-ready data products.

Requirements

Requires a degree in Computer Science or a related field and 5+ years of experience delivering production-grade data pipelines. Proficiency in Python, SQL, AWS, and Databricks is essential, along with the ability to travel to New Haven, CT.

Key skills

• Python — in 1200 other listings on The Stack
• SQL — in 545 other listings on The Stack
• AWS — in 802 other listings on The Stack
• Databricks — in 46 other listings on The Stack
• Delta Lake — in 22 other listings on The Stack
• Data Pipeline Orchestration — not in any other listing on The Stack
• Data Modelling — in 24 other listings on The Stack
• Data Mesh — in 7 other listings on The Stack
• API Development
• ETL
• Life Sciences Data Engineering
• Cloud Infrastructure

On The Stack (as of 2026-11-05)

• AstraZeneca has 1 other listing on The Stack, 1 of them marked as offering visa sponsorship.
• 37 visa-sponsored jobs in Ireland on The Stack, posted in the last 60 days.
• 47 visa-sponsored data engineer jobs in Europe on The Stack, posted in the last 60 days.

Frequently asked questions about AstraZeneca

Is this Senior Data Engineer — Lab Data Pipelines & Data Mesh (12 month FTC) role still open?

It was posted on 2026-07-17. Listings more than 30 days old may no longer be active, so check AstraZeneca's site before applying.

Does AstraZeneca offer visa sponsorship?

This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on AstraZeneca's site.

Where is this role located?

The listing gives the location as Ireland. It is marked on-site.

What skills does this role ask for?

The listing names: Python, SQL, AWS, Databricks, Delta Lake, Data Pipeline Orchestration, Data Modelling, Data Mesh, API Development, ETL, Life Sciences Data Engineering, Cloud Infrastructure.