Senior Data Engineer

Harnham; City Of London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Harnham in London seeks a Senior Data Engineer to lead medical imaging and AI data pipelines. You will build scalable ETL/ELT processes for DICOM and related datasets, leveraging GCP and modern data warehousing concepts.

You will collaborate with ML engineers and scientists to shape data onboarding, validation, and quality controls, applying best-practice software engineering, testing, and documentation to production systems.

Qualifications

• Experience in Python data engineering and data transformation.
• Design and operate ETL/ELT pipelines with orchestration frameworks.
• Strong SQL skills including data modeling and schema design.
• Experience with large-scale datasets in cloud storage (GCP/AWS/Azure).
• Familiarity with CI/CD, DevOps, and modern software engineering principles.
• Ability to work independently in ambiguous environments and make sound decisions.
• Exposure to medical imaging data (DICOM) is highly desirable.
• Experience with GCP, BigQuery, Parquet and cloud-native architectures is beneficial.

Responsibilities

• Build, operate, and automate data pipelines for large-scale medical imaging datasets (DICOM).
• Design cloud-based data ingestion, transformation, and storage solutions on GCP.
• Create automated processes for imaging data onboarding, validation, harmonisation, QC, and de-identification.
• Manage imaging-derived artefacts, linking annotations to source data and delivering analysis-ready datasets.
• Develop production-quality Python code with testing, monitoring, and documentation.
• Collaborate with ML/Software engineers and scientists to optimise datasets and apply AI-driven data quality approaches.

Skills

Python ETL

ETL/ELT pipelines

SQL Data Modeling

Cloud Data Storage

CI/CD/DevOps

Independent Problem Solving

DICOM Imaging

GCP/BigQuery

Parquet & Cloud-Native

IaC

Healthcare Data Governance

Tools

GCP

BigQuery

Parquet

CI/CD Tools

Job description

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.