Senior Data Engineer

Location: Remote-first (1-4 days per month in Bristol)
Type: Full-time, permanent
Salary: Flexible DOE + benefits 

This BioAI scale-up is on a mission to tackle one of the world’s most urgent health challenges: treating life-threatening infections. With a cross-disciplinary team spanning machine learning, genomics, and biology, they’re developing tools that have the potential to save countless lives.  

The company has already assembled strong lab and engineering teams and is now expanding its computational science group to strengthen the data infrastructure that underpins its ML-driven discovery efforts. 

The Role 

We’re hiring a Senior Data Engineer to build and scale the infrastructure that enables machine learning on genomic datasets. You’ll design and maintain robust pipelines for ingesting, curating, and serving large-scale data – ensuring clean, reliable inputs for downstream ML and bioinformatics teams. 

This is a hands-on role for someone who enjoys end-to-end ownership: from designing architecture through to implementation. You’ll be working across cloud environments, occasionally on-prem, and will play a central part in how the organisation manages and unlocks value from its data. 

What You’ll Do 

• Build and maintain ETL pipelines for genomic and life sciences data 
• Design scalable infrastructure to support ML training and bioinformatics workflows 
• Evaluate and implement the right tools, frameworks, and architectures for the job 
• Manage data storage, curation, and access across cloud and local environments 
• Collaborate closely with ML engineers, software developers, and bioinformaticians 
• Contribute to infrastructure strategy as the team scales 

What We’re Looking For 

Required 

• Proven experience building ETL pipelines and data infrastructure in production 
• Hands-on work across cloud platforms (GCP preferred, with exposure to AWS/Azure) 
• Strong software engineering skills, with the ability to choose appropriate tools/architectures 
• Experience with data storage, management, and versioning at scale 
• Ability to work independently, engaging with stakeholders to understand needs and deliver solutions 

Nice to Have 

• Familiarity with life sciences or genomic data 
• Prior experience in a start-up or mission-driven environment 
• Comfort wearing a “DevOps hat” where needed – e.g. infrastructure automation, CI/CD 
• Exposure to using AI or large language model (LLM)–based tools to streamline engineering workflows or accelerate R&D 

Why Join? 

• Play a core role in building the data backbone of a fast-growing biotech 
• Work on problems with direct real-world impact on human health 
• Join a close-knit, multidisciplinary team united by a clear and urgent mission 
• Be part of a company at an exciting growth stage with plans to expand its computer science team over the next year 

Apply now for immediate consideration, or get in touch for questions about this and other roles in the data science and data engineering sector.