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.

Reward and Benefits

£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

About the role

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.

Team Leadership & Delivery

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

Technical In