Research Data Engineer (91325)

Reference: JUL20265919 Expiry date: 17:59, Wed, 15th Jul 2026 Location: Liverpool Salary: £33,951.00 - £38,784.00 Per Annum Benefits: 30 days annual leave, plus bank holidays, plus Christmas closure days Duration: Fixed-term appointment for 18 months

Full-Time, Fixed-term appointment for 18 months

Based in Liverpool with occasional international travel

The Liverpool School of Tropical Medicine (LSTM) is recruiting a Research Data Engineer to support the curation of cloud-based genomic data and maintenance of computational resources for malaria vector research, surveillance, and control.

The successful candidate will join the MalariaGEN Vector Team working on the Vector Observatory project, which aims to improve access to large genomic datasets, develop technologies for their analysis, and support interpretation for public health applications. The role involves developing and maintaining cloud-native genomic data resources, bioinformatics pipelines, and computational infrastructure.

Given the multidisciplinary nature of the project we welcome applications from candidates who hold a post-graduate degree in a range of fields including Bioinformatics, Computer Science, Engineering and Genomics. Previous experience working with disease vector data is not essential and we encourage all applicants interested in large-scale data management, computational design and resource management, and genomics data to address important public health issues.

Key responsibilities will include:

Curate and optimise cloud-native genomic data resources

Curate large-scale genomic data resources related to malaria vectors.

Maintain quality through data and code management best practices.

Support the implementation of data standards, including access, sharing and governance compliance.

Build and maintain tools, resources and bioinformatic pipelines

Build, test and implement scalable genomic-based computational workflows and tools.

Contribute to the deployment and improvement of containerised code and computational environments to ensure analysis reproducibility.

Maintain computational resources to enable data processing.

Provide domain-specific technical support internally and externally

Write and improve internal technical documentation and user-focused resources to support best practices.

Support students and researchers working on similar topics, particularly in troubleshooting code, resolving bugs and issues to facilitate data use.

Contribute to workshops, hackathons and training to support partners and collaborators.

Generate ideas, data and code to support project technical improvements.

Ideally you will demonstrate:

Post-graduate degree in Bioinformatics, Computer Science, Engineering, Genomics; or fields alike

Experience of large-scale data management, including strong programming skills, ideally in Python

Experience with cloud computing environments or distributed computing platforms

Experience managing container-native workflows

Experience or knowledge of next generation sequencing technologies and bioinformatics (desirable)

Experience deploying data products on-premises, cloud, and/or hybrid setups (desirable)

(For a full list of essential and desirable criteria please refer to the job description and person specification)

Informal enquiries can be made to: Anastasia.Hernandez-Koutoucheva@lstmed.ac.uk

Additional benefits of joining LSTM:

Access to support for your career growth through a variety of internal and external learning and development opportunities

Employee Assistance Platform offering a range of wellbeing initiatives and support, in addition to high-street discount offers

30 days annual leave, plus 8 UK bank holidays, in addition to 6 Christmas closure days

Generous occupational pension schemes including USS (Universities Superannuation Scheme) and NHS pension schemes (subject to eligibility)

Government backed “cycle to work” scheme

Affiliated, discounted staff membership to the University of Liverpool Sports Centre

A range of enhanced family friendly policies

Application Process: To apply for this position please follow the apply link and upload your CV, complete our application form and attach a covering letter outlining your interest in the post, and how your skills and experience align.

Due to the volume of applications we receive, we may sometimes close our vacancies early. It is therefore advisable to apply as early as possible if you would like to be considered for a role.

Please click here to learn important information about applying for a position at LSTM.