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A biotech start-up is seeking its first Data Engineer to shape data architecture and strategy. This role involves designing scalable data pipelines for genomic data and collaborating with scientists to enhance data accessibility. Join a purpose-driven team with flexible, remote-first culture and competitive salary.
We’re working with a biotech start-up that’s tackling one of modern medicine’s biggest challenges. They’ve built a next-generation diagnostic device and with AI, machine learning, and their own DNA sequencing tech in play, they’re solving incredibly complex problems at the intersection of science and software.
What you’ll be doing:
Following a successful product launch and securing Series A funding, they’re scaling fast and now looking for their very first Data Engineer. You’ll take the reins on all things data - shaping the architecture, strategy, and pipeline design that supports a life-saving platform.
You’ll be leading on the design and implementation of scalable, secure data pipelines - getting experimental and genomic data into formats that data scientists and machine learning engineers can easily work with. This role combines classic data engineering work with data management strategy, data lineage tracking, and storage infrastructure design; from cold archiving through to high-speed access for ML models, you’ll be the go-to person.
You'll be collaborating closely with engineers and scientists, helping to bridge the gap between their experiments and actionable data. That might mean streaming data off DNA sequencers, integrating with LIMS systems, or improving how they trace results back to original experiments.
This is a great opportunity for someone looking to step up into a lead role with real autonomy, and to shape how data is handled across the company.
What experience you’ll need to apply: