Engineering Manager, Scientific Software

Engineering Manager, Scientific Software

(Senior Data Analyst Manager)

Do you enjoy leading engineers who turn raw scientific data into software the rest of the business can rely on?

We're looking for an experienced Engineering Manager to lead our Data Analysis team - so named for what the product delivers to customers, though the team itself is a software and algorithm engineering team - building the applications that turn raw atomic force microscope (AFM) scan data into the 3D measurements our customers depend on. This is a pivotal role combining hands‑on technical leadership with people management - shaping our software strategy and driving delivery across a growing, cross‑functional organisation.

Our software runs inside semiconductor fabs and processes real 3D height‑profile data captured at atomic scale, so this role suits someone who enjoys working at the forefront of technology on complex problems, scientific data, and software that must be robust, reliable, and trusted by customers.

• £70,000 – £80,000 (depending on experience)
• Death in service and private health care benefits, discretionary annual bonus scheme and a generous EMI Share scheme
• Annual salary review and the opportunity to work on genuinely innovative semiconductor technology

You’ll lead the team that builds our image‑analysis application: consolidating multiple data streams from the microscope, flattening and correcting scan images, recognising scanned features and measuring their height, and running statistical analysis across large sets of measurements. Because the software runs inside a fab with no internet access, the team owns the full picture – there's no cloud service to lean on, so the algorithms, the application, and the visualisation all must hold up entirely on their own.

• Leading, mentoring and developing a team of scientific software engineers, enabling them to deliver high‑quality, fault‑tolerant software in a time‑sensitive product environment
• Owning the team’s software strategy, and shaping how the team works and how our image‑processing algorithms, application architecture and tooling evolve
• Coaching team members through 1:1s, appraisals, hiring and career development
• Working with project leads to plan, track and report progress, and integrating the team’s work into wider programme plans
• Managing technical debt pragmatically, balancing delivery speed against long‑term maintainability
• Improving engineering processes so the team can keep getting better, drawing on Agile and Lean practices

• Staying hands‑on technically where capacity allows – reviewing code, unblocking algorithm and architecture decisions, and staying close to the data
• Working closely with the R&D team to translate good image processing methodology into quality product. Guiding decisions on image‑processing approaches (flattening, feature recognition and masking, skew correction, height measurement etc.) and on the statistical analysis of measurement data
• Ensuring the application, its communication interface (over RabbitMQ) and its data visualisation are engineered to run reliably in an offline, on‑premises fab environment with no cloud dependency

• Collaborating closely with the Software Project Lead and R&D, Systems Engineering, Product and Applications teams to keep priorities aligned
• Managing external partners where they support delivery

A note about AI: we’re adopting agentic development with Claude, but our engineers retain full ownership and accountability of the code they ship - whether they wrote it or generated it. AI is a tool that amplifies engineering expertise, not a substitute for it.

To succeed as an Engineering Manager,…