Title:

Senior Data Engineer - Healthcare AI

Location:

UK or Europe | Remote (±2–3 hrs GMT overlap mandatory)

Reports to:

Head of Engineering

Existing Clients:

Top 100 Lifesciences, MedTech and Pharma companies

Type:

Full-time

Core responsibilities & objectives

• Design, build, and maintain batch/streaming data pipelines, ingestion, cleaning, normalisation, enrichment, deduplication.
• Build and own ML/LLM pipelines end-to-end: document parsing, chunking, embeddings generation, vector indexing, agentic tool calling, multi-step workflows, retries, fallbacks, and state handling.
• Write production-grade, well-tested Python that processes large volumes of data and documents reliably.
• Own pipeline health: if data is stale, broken, or wrong, it's on you.
• Work autonomously to project deadlines with minimal hand-holding.

Key qualifications & skills (non-negotiable)

• 7+ years in backend data-heavy development or data engineering.
• Highly proficient in Python
• Hands-on experience with large datasets and high-velocity data streams (Kafka, Flink, Spark).
• Strong with pipeline orchestration tools (Airflow, MLflow, or equivalent).
• Solid SQL skills (Postgres, BigQuery, or Snowflake) and NoSQL experience (DynamoDB, OpenSearch, Elastic).
• Real experience with LLM workflows: RAG architectures, embeddings/vector DBs, prompt engineering, function/tool calling, observability.
• Deep understanding of ETL/ELT patterns and data processing at scale.

Preferred background (strong signals)

• Experience with AWS data stack at scale.
• Exposure to healthcare, life sciences, or regulated industries.
• Built and shipped data, ML and LLM-powered pipelines in production.
• Has debugged a pipeline and knows why observability matters.
• Worked in a fast-moving startup where "that's not my job" doesn't exist.

What will get you rejected

• "I set up the pipeline, someone else monitors it" mindset.
• Tutorials and side projects but no production experience at scale.
• Can't explain trade-offs between streaming vs. batch, or why you chose one vector DB over another.
• Needs detailed specs before writing a line of code.
• No curiosity about healthcare or what the data actually means.

Interested?

We're a distributed team solving hard problems that will reshape the healthcare industry for a generation. If you want ownership, not just tickets, we'd like to hear from you.