Data Engineer

Qureight Ltd; Cambridge; On-site; GBP 80,000 - 110,000; Full time

Benefits offered by this job

Annual bonus plan

Private medical insurance

Cycle-to-work scheme

Contributory pension scheme

Equity

Job summary

Qureight Ltd in Cambridge is expanding its Data Engineering team to design, build and maintain trial-specific data pipelines that process DICOM imaging and clinical metadata. You will collaborate with Clinical Operations, Infrastructure and Data Science to automate data workflows within regulatory boundaries and deliver reproducible, compliant results.

The Senior Data Engineer will drive scalable pipelines, validate data quality, and contribute to pipeline framework decisions while mentoring

Qualifications

• 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.

Responsibilities

• 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.

Skills

Python

DICOM imaging

Data pipelines

Regulated environments

AWS

Dagster

Kubernetes

GitOps

Tools

Git

Kubernetes

Job description

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
• 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

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.