Scientific Data Engineer - Tech Lead

QP Group is working with a fast-growing data and AI business focused on transforming how life sciences organisations use scientific data. Its cloud platform brings together laboratory and R&D data at scale, and pairs it with in-house scientific expertise to help biopharma customers get to better results faster.

Culture

The company places real emphasis on openness, giving its people the information and context they need to make good decisions. Honest communication and trust are central to how teams work together. It looks for people who lean into difficult problems, are comfortable with ambiguity, and are willing to take considered risks. Customer success sits at the heart of the business, as does a strong pride in doing the detail well. It is also committed to hiring outstanding people from all backgrounds who bring fresh perspectives to the team.

The Role

This is a hands-on leadership position heading up a team of data engineers who build the data products and solutions that underpin the company's platform. The successful candidate will combine technical delivery with people leadership, mentoring less experienced engineers, running design discussions, writing code, and taking projects all the way through to production.

They will partner closely with product managers, business analysts and solution architects to shape requirements and translate them into working solutions for customers. The role suits someone who enjoys leading from the front, cares about getting implementations right for customers, and works well within a collaborative, well-supported environment.

Key Responsibilities

• Leading and developing a team of data engineers, including managing performance and career progression
• Owning end-to-end delivery across multiple customer projects
• Collaborating with cross-functional colleagues to define requirements, propose options and agree the best approach
• Designing and building data models, pipelines and applications that deliver measurable value for customers
• Applying LLMs to create data schemas and parsers for pre-clinical data from lab instruments, manufacturing, external research and manufacturing partners, and lab informatics systems, across a wide range of file types including proprietary instrument formats
• Turning reusable parsing logic and schema components into maintainable Python libraries
• Ensuring pipelines are robust and well tested, with strong unit and integration test coverage
• Building dashboards, reports and data applications using tools such as React, Streamlit and Jupyter
• Confirming delivered solutions meet customer needs and set a high bar for quality
• Championing improvements to engineering processes, tooling and developer experience
• Keeping the team on track against sprint goals and tackling blockers and inefficiencies quickly

Requirements

• 10+ years' experience in data engineering or a closely related field
• Extensive Python and SQL experience in data-focused roles
• Proven experience leading technical projects, managing requirements and delivering to deadlines
• Experience running several customer-facing projects in parallel with cross-functional teams
• A track record of improving engineering standards and delivery efficiency
• Experience with React and/or Streamlit for dashboards and visualisation (highly desirable)
• Experience with pre-clinical data and working alongside lab scientists (highly desirable)
• Strong communication skills, attention to detail and confidence owning delivery
• The ability to get to grips with a complex technical product quickly and communicate clearly with product and engineering teams

Benefits

• Fully employer-funded healthcare cover for employees and their families
• 401(k) plan
• Unlimited holiday
• Life insurance and disability cover