Senior Data Engineer

Senior Data Engineer (Medical Imaging & AI)

London | 12 Month Contract

The Company

They are a technology-driven organisation using advanced AI and Machine Learning to solve complex challenges in healthcare and life sciences. Their teams bring together data, engineering, and scientific expertise to develop innovative solutions that support research and drug development. As they continue to scale their AI capabilities, they are looking for an experienced Data Engineer to support a critical imaging data initiative.

The Role and Deliverables

• Build, operate, and automate data pipelines for large-scale medical imaging datasets, including DICOM and associated tabular data.
• Design and develop cloud-based data ingestion, transformation, and storage solutions on GCP.
• Create automated processes for imaging data onboarding, validation, harmonisation, quality control, and de-identification.
• Manage imaging-derived artefacts, linking annotations and segmentations to source imaging data and delivering analysis-ready datasets.
• Develop production-quality Python code with strong testing, monitoring, and documentation practices.
• Collaborate with ML Engineers, Software Engineers, and scientific stakeholders to optimise datasets and apply AI-driven approaches to data ingestion and quality assurance.

Your Skills & Experience

• Strong Python data engineering experience, including data transformation, monitoring, and schema management.
• Experience building and operating ETL/ELT pipelines using orchestration frameworks.
• Strong SQL skills, including data modelling and schema design.
• Hands-on experience working with large-scale datasets in cloud object storage environments such as GCP, AWS, or Azure.
• Experience with CI/CD, DevOps practices, and modern software engineering principles.
• Ability to work independently in ambiguous environments and make sound technical decisions.
• Exposure to medical imaging data, particularly DICOM, is highly desirable.
• Experience with GCP, BigQuery, Parquet, cloud-native architectures, and Infrastructure as Code is beneficial.
• Knowledge of AI-assisted software development, healthcare data governance, or clinical data environments would be advantageous.