This assignment involves developing and operationalizing secure data and integration components that connect hospital research registries with environmental and socioeconomic data. You will work closely with the ICT department of a hospital, supporting their clinical teams and data scientists from a research institution. The project studies how combinations of environmental exposures, socioeconomic factors, and health characteristics influence cardiovascular, neurovascular, and other non-communicable diseases.
A core requirement is a privacy-preserving technical ecosystem that can securely and reproducibly enrich pseudonymized hospital records with exposomic data.
What you will do.
- Contribute to the development of data-driven products: from the Clinical Data Warehouse to innovative applications of AI and Data Science.
- Build a solid DataOps framework that supports the entire lifecycle of data-intensive products via data pipelines – from efficiently extracting data from various sources to smoothly operationalizing it in a production environment.
- Technically design and develop the REDCap integration framework around a hospital's REDCap environment for secure handling of structured, unstructured, and non-textual research data.
- Contribute to the development of the novel Digital Health Data Platform of the research institution and the hospital, which makes data available to various stakeholders.
- Implement reliable interfaces and data pipelines between REDCap and a central server, including privacy-preserving geocoding and automated enrichment of patient records with environmental and socioeconomic data for defined locations and time windows.
- Collaborate with and support researchers, clinicians, data managers, IT engineers, and data-protection stakeholders to refine requirements, resolve integration issues, support deployment and end-user adoption, and contribute to the REDCap Ecosystem and reference-architecture deliverables.
Profile
- At least a bachelor's degree in a scientific IT-oriented field (engineering, computer science, sciences, …).
- A few years of relevant work experience in Data Engineering and Data Ops is preferred.
- Experience with tools such as Docker, Git, Jenkins, and Prefect.
- Experience in an ETL / ELT environment.
- Setting up and managing a Data Warehouse / Data Lake is an advantage, as is familiarity with Microsoft Azure data services.
- Good knowledge of programming in Python and SQL is a must.
- High value placed on good software design, applied in concrete projects.
- Experience with REDCap, electronic data-capture systems, research registries, or hospital data environments is a strong asset.
- Clear communication with both technical and non-technical stakeholders and the ability to translate clinical/research needs into implementable technical solutions.
- Work effectively in a multidisciplinary team while also being able to work independently.
- Analytical, good communication skills, a team player, and able to work independently.
- High regard for privacy and ethics.
How to apply
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