Data Engineer
Summary
Data Engineer at an early-stage HealthTech startup in London building a data intelligence platform for pharma and life sciences, owning the production data pipelines behind the product. Day to day: building ETL/ELT pipelines in Python and SQL and applying LLM/AI workflows to extract, clean and validate large volumes of messy healthcare data. On-site at least 4 days a week; equity offered.
Data Engineer | AI-Driven HealthTech | London | £60k-£90k + Equity
I’m working with a fast-growing, early-stage HealthTech business building a data intelligence platform for the pharmaceutical and life sciences industry.
They’re now hiring a permanent Data Engineer to join a small engineering team and take real ownership of the data pipelines that sit behind the product.
This isn’t a role maintaining an established warehouse or simply working through a backlog of tickets. You’ll be working with large volumes of messy, complex healthcare data, building and refactoring production pipelines, and using AI within those workflows to extract, classify, clean and validate information.
What they’re looking for:
- Strong Python and SQL
- Experience building ETL/ELT pipelines in production
- Comfortable working with structured and unstructured data
- Experience with LLM APIs / AI-powered data workflows would be highly relevant
- Exposure to scraping, data acquisition, schema design, deduplication or entity resolution
- Healthcare, pharma or life sciences data experience is a big advantage
- Someone autonomous, curious and comfortable figuring things out in an early-stage environment
They’re much more interested in what you’ve owned and built than a specific number of years’ experience.
London, minimum 4 days a week on site
Equity available
They’re looking for someone who genuinely wants to help build a company, take on responsibility and be part of a high-growth startup environment.
A really good opportunity for a Data Engineer who wants more ownership, direct product impact and exposure to applied AI rather than being one engineer in a huge data function.