Senior Clinical Data Engineer Reproducible AI Pipelines

Qureight Ltd; Cambourne; On-site; GBP 80,000 - 120,000; Full time

Benefits offered by this job

Annual bonus

Private medical insurance

Life insurance

Cycle to work

Pension scheme

Equity

Job summary

Qureight Ltd in the United Kingdom is seeking a Senior Clinical Data Engineer to transform incoming clinical trial data into standardised, analysis-ready datasets. You will build reproducible data pipelines that take repetitive data work away from our Data Scientists, increasing output and ensuring traceability to inputs, code and parameters.

You will work alongside Data Scientists and Data Engineers, developing pipelines using Dagster and cloud infrastructure (AWS), applying CDISC SDTM/ADaM

Qualifications

• Experience as a Data Engineer or clinical data programmer.
• Hands-on with CDISC standards (SDTM/ADaM) in trials.
• Experience handling sponsor/CRO data transfers and EDC extracts.
• Strong Python in a commercial setting (pandas, NumPy, pytest).

Responsibilities

• Prepare clinical trial data to study transfer specifications.
• Build analysis-ready datasets (ADaM-style) from agreed specs.
• Design, build and maintain reproducible data pipelines (Dagster).
• Deliver CDISC formats (SDTM/ADaM) when required.
• Automate repetitive analytics steps with Data Scientists.
• Ensure versioning, lineage and validation checks in pipelines.
• Develop shared tooling and templates for analyses.

Skills

Data Engineer experience

CDISC SDTM/ADaM

Python pandas

CI/CD pipelines

Data validation

Dagster

AWS

Data science workflows

Collaboration

Tools

Dagster

Docker

Kubernetes

MLflow

DVC

Job description

Qureight Ltd in the United Kingdom is seeking a Senior Clinical Data Engineer to transform incoming clinical trial data into standardised, analysis-ready datasets. You will build reproducible data pipelines that take repetitive data work away from our Data Scientists, increasing output and ensuring traceability to inputs, code and parameters.

You will work alongside Data Scientists and Data Engineers, developing pipelines using Dagster and cloud infrastructure (AWS), applying CDISC SDTM/ADaM