Job Description
An early-stage health technology company is seeking a Clinical Data Engineer to help build and maintain the data infrastructure underpinning a novel class of wearable health biomarkers.
This is a highly impactful role within a close-knit team, where you'll work at the intersection of clinical research and data engineering - collaborating with clinicians, researchers, and ML teams to ensure that raw physiological signals are transformed into trustworthy, analysis-ready datasets. You'll play a key role in shaping how wearable health data is validated, governed, and deployed at scale.
In this position, you'll be responsible for designing and implementing multimodal data pipelines, cleaning and synchronising real-world clinical datasets, and building tooling for annotation, quality control, and versioning. You'll also support clinical study design and ensure all data processes meet regulatory and privacy requirements.
What they're looking for:- Strong experience with time-series data engineering and analysis
- Proficiency in Python and relevant data frameworks
- Experience working with clinical or biomedical datasets
- Solid understanding of data quality, bias, and reproducibility in health research
- Ability to collaborate effectively across clinical and engineering stakeholders
- Familiarity with data governance, privacy standards, and audit requirements
- Opportunity to build the clinical evidence foundation for a genuinely novel area of wearable health technology
- High level of ownership and influence over data infrastructure and research workflows
- Collaborative environment spanning clinical, research, and ML disciplines
- Work that directly shapes how wearable health data is trusted and interpreted at scale
