Data Engineer – Science

Qureight

Senior Data Engineer preparing and managing large imaging datasets for AI-driven imaging platform. Collaborating with machine learning scientists and engineers to design data infrastructure.

Posted 5/19/2026full-timeCambridge • 🇬🇧 United KingdomMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AWSCloudDockerFluxKubernetesPython

About the role

Key responsibilities & impact

**What you will do**
- Collaborate on designing and implementing new data infrastructure and pipelines preparing data for large-scale ML workflows
- Care about data quality, and ensuring the pipelines you build are robust, scalable, and maintainable
- Work with DICOM data to feed into foundation model and disease-specific imaging model development
- Collaborate closely with Machine Learning Scientists, DevOps Engineers, and other Data Engineers to create a tight feedback loop and ensure the end-to-end process is effective and efficient
- Ensure that our data processes have quality and compliance designed in from the start to make reproducibility, lineage tracking, and data quality painless
- Scale pipelines to handle millions of scans – ingesting the imaging data, transforming it, filtering and structuring ready for foundation model development.

Requirements

What you’ll need

**What we need...**
- Proven experience as a Data Engineer in complex, data-rich environments
- Strong programming skills in Python
- Experience building and maintaining production ML data pipelines, including orchestration tools such as Dagster and cloud infrastructure on AWS
- Experience with Docker and Kubernetes based infrastructure Experience working with large datasets
- Understanding of data preprocessing and quality control for machine learning
- Strong collaboration skills with machine learning or technical teams
**Even better if you have experience of...**
- Medical imaging data such as CT, MRI, or DICOM
- Large-scale datasets or foundation model workflows
- Deployment tooling (Helm and familiarity with Gitops tooling such as Flux and Kustomize)
- Data versioning and reproducibility frameworks
- Database design and data modelling
- Working in regulated or GxP or ISO 13485 environments
- Experience with ML experiment tracking or metadata management (MLFlow)

Benefits

Comp & perks

- A comprehensive benefits package that includes an annual bonus plan, private medical insurance, life insurance, and a contributory pension scheme
- 25 days annual leave, plus bank holidays and enhanced maternity 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.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Pythondata engineeringML data pipelinesdata preprocessingquality controldatabase designdata modelingdata versioningmetadata managementlarge-scale datasets

Soft Skills

collaborationcommunication