Lead DevOps Engineer - Department for Science, Innovation & Technology - G7
Government Digital & Data -
Location
Bristol, London, Salford
About the job
Job summary
At DSIT we’re all about improving people’s lives by maximising the potential of science & technology.
We accelerate innovation, investment and productivity through world-class science, research and development.
We use technology for good by ensuring new and existing technologies are safely developed and deployed across the UK, with the benefits more widely shared.
We are driving forward a modern digital government which gives citizens a more satisfying experience and their time back.
We do all this to enable the Government’s 5 national missions: kickstarting economic growth, making Britain a clean energy superpower, taking back our streets, breaking down barriers to opportunity and building an NHS fit for the future.
Above all, we focus on improving people’s lives. Whether it’s researching new treatments for disease, developing better batteries, reducing burdens through better public services, keeping children safe online, and much more, outcomes for citizens are at the heart of what we do.
Our Inclusive Environment
We offer flexible working benefits, employee well-being support and a great pension. We are enormously proud to be a Disability Confident Leader employer. We support candidates with adjustments throughout our recruitment process. Information about disability confidence and just some examples of the adjustments that you can request can be found in the reasonable adjustment section below.
Please note
Former DSIT recruitment campaigns are continuing as usual, but candidates should be aware that following the Government’s announcement on the changes to some civil service departments, roles will be subject to the machinery of government moves and will ultimately be in one of the new departments. We will provide more information if you are selected for a role. This work remains of high importance to the civil service, and we thank you for your continued interest.
Job description
We are building a modern, unified analytical tooling and data platform, giving analysts across the department access to tools and data quickly and securely. The platform is based on the Ministry of Justice’s open-source Analytical Platform, widely recognised as a leading model across government. The team have completed user acceptance testing and are preparing to migrate analysts onto the platform, however there are plenty of new features to be added and we are setting up a short feedback cycle with our users, to rapidly iterate the platform.
The project is led by the Head of Platforms and Engineering, and the team brings expertise across data engineering, dev ops and software development. We are a small team with lots of autonomy and work collaboratively to tackle problems and decide on the best ways of working. For the right candidate, there will be the opportunity to take on a leadership role within the team.
The platform is made up of several components, divided into two sections:
- Analytical tooling – delivering the secure, scalable tools analysts need, such as JupyterLab, RStudio, and VS Code, GitHub integration, and cloud-based workflow orchestration.
- Data platform – delivering the pipelines, storage, and ingestion processes that ensure analysts can find and use trusted data efficiently.
The role is part of the central Data Science and Engineering team, in the department’s Analysis function. This team plays a key role in shaping the department’s analytical capability. By sitting within Analysis, the team ensures the platform is developed with analysts’ needs front and centre, owned by the analytical community and built to serve it.
As a G7 Lead DevOps Engineer in the analytical tooling strand of the project, you will own and extend the infrastructure and tools that enable analysts to work securely, reproducibly and efficiently. You’ll take forward the platform to ensure it is a secure, cloud-based environment for analysis at scale, drawing on best practice across government. Your work will directly improve evidence-based policymaking, unlock efficiency savings across the department, and create the foundations for future innovation and AI based policymaking.
The team are led by the needs of our users, and initially this role will focus on strengthening and extending the analytical tooling infrastructure. As the platform matures, you’ll also have opportunities to tackle broader DevOps challenges across the department, including data science and AI applications that improve operational efficiency and widen access to data for non- technical users.
Person specification
- Manage secure, scalable deployments of key analytical tools, including JupyterLab, RStudio and VS Code.
- Ensure authentication, access controls, monitoring, and audit capabilities are in line with DSIT and cross-government security standards.
- Ensure robust CI/CD (GitHub) and environment management processes are in place.
- Work closely with Data Engineers and wider digital colleagues to ensure seamless integration between tooling and data systems.
- Extend the analytical platform, developing new features to meet user requirements such as dashboard hosting and AI applications.
- Support onboarding of users and act on feedback to refine the platform for wider rollout.
Essential Criteria
- Strong experience designing and delivering secure cloud-based infrastructure (AWS preferred).
- Proficiency in containerisation and orchestration (e.g. Docker, Kubernetes, AWS ECS/Fargate).
- Proficiency setting up infrastructure-as-code (Terraform preferred).
- Ability to set up CI/CD pipelines.
- Knowledge of information security and access control in cloud services.
- A collaborative approach to working with data engineers, software developers, service designers and users to shape fit-for-purpose tools.
Desirable Criteria
- Experience with Python and Django applications.
- Familiarity with analytical user requirements and how to build user-friendly analytical platforms.
- Familiarity with analytical tools (e.g. JupyterLab, RStudio, VS Code) and how they are deployed in cloud environments.
