Data Engineer
Summary
A Data Platform Engineer designs and owns a governed data platform on Azure (Databricks, containerized Python workflows) that underpins clinical studies, algorithm development, V&V, and future post-market monitoring for a needle-free glucose monitor, ensuring traceability and audit-friendly data practices alongside clinical, algorithm, embedded, and quality teams.
GlucoModicum is developing a needle-free glucose monitor that has recently reached product freeze and is now in Verification & Validation (V&V) for CE marking.
Our mission is to transform diabetes management through non-invasive glucose monitoring, thereby improving the lives of more than 400 million people worldwide who live with diabetes.
About the Role
We are looking for a motivated Data Platform Engineer to build and own the data platform that supports clinical studies, algorithm development, verification & validation activities, and future real-world device monitoring.
This is a unique opportunity to shape the data foundations of a medical device as it moves toward market launch. The platform will connect clinical datasets, validation evidence, device configurations, firmware versions, and algorithm releases, providing the traceability required for both product development and future post-market surveillance.
You will work closely with clinical researchers, algorithm scientists, embedded software engineers, and quality and regulatory teams.
Responsibilities
- Design and implement a governed data platform on Azure using technologies such Databricks and containerized Python workflows.
- Build reproducible data and analysis pipelines for clinical studies, R&D, and validation activities.
- Implement data quality controls, lineage tracking, audit-friendly records, and privacy-aware data handling practices.
- Support traceability across datasets, devices, firmware versions, configurations, and algorithm releases.
- Establish engineering standards, CI/CD practices, testing strategies, and platform governance.
Required Skills
- Strong Python software engineering skills.
- Experience building production data platforms, pipelines, or analytics systems.
- Experience with cloud platforms, preferably Azure.
- Experience with workflow orchestration tools such as Dagster, Airflow, or Prefect.
- Experience with Docker, Git, CI/CD, and reproducible execution environments.
- Strong understanding of software engineering best practices.
Bonus Skills
- Experience in medical devices, digital health, clinical research, or other regulated environments.
- Experience supporting reproducible scientific, clinical, or validation workflows.
Why Join Us?
Few engineers get the opportunity to build a data platform before a medical device reaches market. Your work will directly support clinical evidence generation, algorithm validation, regulatory submissions, and future post-market surveillance for a breakthrough healthcare technology.