Scientific Data Engineer

Epoch Biodesign is a global leader in enzymatic recycling, with a unique ultra-low emission process capable of producing virgin-quality materials from mixed waste streams. Epoch is currently building Europe's first - and the world's largest - nylon 66 biorecycling plant.

In July 2026, Epoch acquired a 52,000 tpa nylon 66 polymerisation facility in Blanes, Spain - vertically integrating the company all the way from waste to chip. Crucially, with the Blanes facility, we are now already taking orders and shipping polymer.

To support our goals, we are looking for an experienced sales leader with an entrepreneurial mindset and a proven ability to win new business, grow market share and build lasting customer relationships across the polyamide market within Europe, the Middle East and Africa.

The Role

As a Scientific Data Engineer at Epoch, you will support Epoch's computational infrastructure by building, maintaining and improving the data pipelines that underpin our R&D activities. Working closely with computational and lab biologists, and with support from senior members of the team, you will learn to gather requirements, prototype solutions and develop robust, reproducible pipelines, helping ensure that data flows reliably from instrument to insight. This is a great opportunity for someone early in their computational career to develop their skills in a supportive, interdisciplinary environment. A background in life sciences with a fluency in python is essential, together with an ability to learn quickly and adapt to changing requirements. Your core activities will include:

• Helping maintain our existing sequence analysis pipeline, with a focus on next-generation sequencing data, under the guidance of senior team members.
• Maintaining and extending our analytics data-processing pipeline, including ingesting data from instrument computers into cloud infrastructure and configuring automated triggers for downstream processing.
• Working with senior engineers to take pipelines built at prototype stage by other team members and help turn them into robust, reproducible, production-ready systems using containerised deployments (Docker).
• Acting as a point of contact with lab biologists, working to understand the nature of their data, their analytical methods, and their requirements for processing, access and visualisation.
• Helping to train colleagues in the use of developed tools and pipelines.

Essential Qualifications & Experience

• Excellent interpersonal skills, with demonstrable evidence of working collaboratively in a team environment.
• A degree in life sciences, with computational biology experience.
• Good working knowledge of Python and common scientific/data libraries (e.g. NumPy, SciPy, Pandas).
• Experience handling and processing scientific data computationally.
• Some experience with cloud-based services (e.g. GCP, AWS, or similar), and an interest in developing further expertise in cloud-based pipeline orchestration.
• Familiarity with Docker and containerised deployment workflows, with a willingness to learn more.
• Some experience with environment and dependency management tools (e.g. Conda, Mamba).
• Familiarity with Git and version control, with awareness of automated testing practices.

Benefits and perks

• A generous allowance of 30 days paid holiday (plus the usual 8 bank holidays)
• Meaningful EMI Share Options
• A non-contributory pension of 9% employer contribution
• Optional company covered private medical insurance with Vitality
• Group Income Protection
• Group Critical Illness
• Flexible working around the core times of 10am to 4pm
• Cycle to work scheme
• The opportunity to be part of building something remarkable

On-the-job

• Complementary fresh fruit, coffee, tea and snacks
• Onsite gym
• Various staff social activities

And we're continuously reviewing and enhancing our benefits and work environment.