Data Engineer (Health Technology) UK Dementia Research Institute (Imperial)

Vacancy Reference Number
Closing Date
17 Apr 2024
£53,927 - £64,935 per annum plus benefits
UK Dementia Research Institute, Department of Brain Sciences, Imperial College London, White City Campus - Hybrid
This is a full-time and fixed term (24 months) role based at the Imperial College White City Campus.

About the job

Dementia is the biggest health challenge of our century.

To date there is no way to prevent it or even slow its progression, and there is an urgent need to fill the knowledge gap in our basic understanding of the diseases that cause it.

The UK Dementia Research Institute (UK DRI) is the biggest UK initiative driving forward research to fill this gap.

The UK DRI at Imperial brings together researchers from diverse backgrounds with fresh perspectives, drawing on the university’s unique strengths, resources and focus on science, engineering, medicine and business. The team recognises that the challenges of dementia demand new concepts, new approaches and a diverse range of new research tools and directions. Their holistic approach views the ageing brain in the context of the ageing body, not in isolation.

 This is a rare opportunity to join a multi-functional team building a unique health technology platform that supports the care of people affected by dementia and other conditions. We are seeking a data and machine learning engineer motivated by the chance to address exciting technical challenges while working on Minder, a project with the potential to deliver positive impact to individuals and broader society. You will have an influential role in designing, deploying, managing and using infrastructure for data analysis as the platform is rolled out in a growing number of care settings.

You will be working alongside dedicated software developers, clinical researchers, data scientists, healthcare professionals and designers. We use an agile development methodology, following industry-standard software and data engineering processes for version control, build automation and continuous delivery. The role is multifaceted and will inevitably evolve as Minder becomes an increasingly intelligent platform, but you can expect to be working on infrastructure and code for data management, analysis and visualisation, alongside supporting the development and overseeing the deployment of machine learning models.

This position is within the?UK DRI Care Research and Technology Centre?at Imperial College London, which has been established to address a medical research area of the highest importance and future impact as one of seven new national centres of excellence embedded in major UK universities. We are looking for a suitably qualified candidate, regardless of background, to become a valued member of a highly capable team based at a prestigious research institution. Imperial College provides enthusiastic and curious individuals with a broad range of employee benefits, including extensive opportunities for personal development.

Duties and responsibilities

On a day-to-day basis you’ll be interfacing with our existing software engineering and data science teams: deploying tools to ensure that up-to-date data is made available to data scientists in useful formats, assisting them to develop and deploy their machine learning models, and providing tools for exploratory data analysis and visualisation.

This will involve responsibility for building the relevant cloud infrastructure i.e. planning, implementation, QA and maintenance and will require knowledge of Python, SQL, cloud data warehouses, workflow orchestration tools and distributed compute frameworks with Kubernetes and/or Azure.

Essential requirements 

  • Degree level qualification in data science, software engineering or related discipline, or equivalent professional experience.
  • Significant experience of data engineering including workflow management platforms, data warehousing solutions and data transformation tools.
  • Use of cloud-native infrastructure.
  • Development of machine learning algorithms/pipelines.

Contact information

To apply visit here.

Should you require any further details on the role please contact Mark Woodbridge or Anna Joffe

For any technical queries, please contact