Live opening · Posted 6 hours ago

Senior Data Engineer

Qureight Ltd · Cambridge, England, United Kingdom
Workable No
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At a glance

The key details from the original listing.

Posted 6 hours ago
CompanyQureight Ltd
LocationCambridge, England, United Kingdom
Work modeNo
SkillsPython, AWS, Kubernetes
SourceWorkable
ListedPosted 6 hours ago

About the role

Description supplied by the original job listing.

About us
Qureight’s mission is to accelerate clinical trials and ensure breakthroughs in lung and heart disease reach patients without delay. Our AI-powered data and imaging curation platform enables the analysis of clinical imaging and other healthcare data, helping our customers bring treatments to market, faster.
We’re looking for talented people who want their work to matter. With offices in Cambridge and London, you’ll join our multidisciplinary team of clinicians, scientists, and engineers. What unites us is our open culture, continuous learning mindset, and a shared mission to help biopharma run faster, smarter trials.
The Data Engineering team prepares the clinical data that our biomarker measurements are built on. We work with medical imaging and tabular clinical data, automating the cleaning, organisation and validation of this data, so that it can be used to quantify precision biomarkers for clinical trial endpoints. We support many sponsors and studies at the same time, so the work is varied. Our team members are involved in a wide range of active clinical trials, covering different therapeutic areas, imaging types and study designs.
About the role
As Qureight expands, we’re running image analytics for an increasing number of clinical trials in multiple disease areas. We’ve developed data pipeline frameworks for processing the data we receive from each trial and for handling data needs that are specific to each trial. We now want to further automate this process and scale to take on even more trials.
The Senior Data Engineer will implement trial-specific data pipelines, working with DICOM imaging. You will work closely with our Clinical Operations team, observing the details of each trial whilst exploring how we can improve our systems and processes within the clinical trial regulatory framework. The focus will always be to ensure efficient, accurate data pipelines that minimise errors and keep data quality embedded by design.
If you are interested in the interface between data infrastructure, software engineering, and medical applications – particularly in clinical trials – then this role is for you.
What you will do
Design, build, test, deploy and maintain trial-specific data pipelines that meet study protocol requirements
Work with Clinical Operations, Infrastructure, Data Science and Data Management teams to build the tooling each trial needs
Handle a wide range of datasets and transfer methods, integrating DICOM imaging (mainly CT) with clinical metadata
Build pipelines that are robust, scalable and maintainable, with quality and compliance designed from the start so that reproducibility, lineage tracking and data validation are straightforward
Own data delivery for your projects and help shape how we automate regulatory compliance
Contribute to technical decisions on our pipeline framework, review colleagues' code and support less experienced engineers
Requirements
What we need
Proven experience as a Data Engineer in complex, data-rich environments
Strong Python skills gained in a commercial setting
Experience building and maintaining production data pipelines within regulated environments
Experience implementing data validation and quality checks in production pipelines
Experience with automation/orchestration tools, such as Dagster and cloud infrastructure on AWS
Strong collaboration skills and attention to detail, with the curiosity to understand where data comes from and how it will be used
Experience working with medical imaging data such as CT, MRI in DICOM format
Even better if you have…
Experience deploying in Kubernetes, particularly using GitOps tools such as Flux
Experience of data versioning and reproducibility frameworks
Experience working in regulated or GxP or ISO 13485 environments, or with clinical trial data
Benefits
What can you expect from us
A comprehensive benefits package that includes an annual bonus plan, private medical insurance, life insurance, cycle-to-work scheme, and a contributory pension scheme
Equity, so that our team can share in the long-term success of Qureight
28 days’ holiday allowance, 25 days’ annual leave and 3 additional company days between Christmas and New Year, plus bank holidays and enhanced family leave
A diverse work environment that brings together experts in many fields, including software engineering, DevOps, data science, machine learning, quality assurance, regulatory affairs, and clinical operations.
How to apply
Please upload a CV and covering letter by clicking 'Apply Now'. Your covering letter should explain why you are applying for the job and what skills and experience you can bring to the role.
We review CVs as we receive them and interview as soon as we have applications that look like a good match (usually within one week). We do not use closing dates. So, please apply as soon as possible to avoid missing out on this role. We advertised this role on Monday 19th October.
If you have any queries, please contact careers@qureight.com.
Everyone is welcome at Qureight. We are an equal opportunities employer and encourage applications from all suitably qualified candidates regardless of age, disability, ethnicity, sex, gender reassignment, religion or belief, sexual orientation, marriage and civil partnership, or pregnancy and maternity.
Women and other underrepresented groups may be less likely to apply for a role unless they meet all or nearly all of the requirements. If this applies to you, we still encourage you to apply – you may be a great fit, even if you don’t meet every qualification. We’d love to hear from you.
If you require any adjustments to the application or selection process, please let us know. We will be happy to support you.

Work arrangement
No

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