Research Data Operations Engineer - Full Time - Hybrid
RetinAI Medical Madrid, Community of Madrid, Spain
Software Development · 11-50 employees
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About the role
You will own the data backbone by building and maintaining pipelines, tooling, and governance for clinical imaging and EHR data. This role involves ensuring data integrity, managing access controls, and supporting researchers with efficient data annotation and search capabilities.
What they look for
Requirements
The role requires a university degree in Computer Science or a related field with at least 3 years of relevant experience, including 2 years in the healthcare sector. Candidates must possess strong Python skills, solid data engineering fundamentals, and experience with data infrastructure and regulated data environments.
Benefits
Full description
About Us
Ikerian AG (formerly RetinAI Medical) is a fast-growing medical device software company headquartered in Bern, Switzerland. Our mission is to enable the right decisions sooner in healthcare, through transformative AI & data management solutions for disease screening and monitoring. Join our diverse team of entrepreneurs, developers, researchers, and commercial experts who are collectively shaping the future of healthcare.
We build AI/ML systems on clinical imaging and patient data. As our Research Data Operations Engineer, you'll own the data backbone our researchers depend on: the pipelines, tooling, and governance that keep thousands of patient images, multiple modalities, and EHR excerpts clean, findable, versioned, and compliant.
Job Description
We are looking for a Research Data Operations Engineer to join our team. This role sits at the intersection of data engineering, ML infrastructure, and data governance. It's hands-on. You will write the scripts, stand up the infrastructure, and own data integrity end to end.
Key Responsibilities
- Create and support EHR extraction, matching and transformation tools
- Support data versioning (DVC) running smoothly, and make updating, tracking, and rolling back datasets routine.
- Build and maintain pipelines and tools to clean, validate, and organize clinical imaging data and EHR excerpts.
- Support the migration from our custom image format to DICOM.
- Make data annotation fast and painless for researchers.
- Set up and manage access controls so the right people reach the right data.
- Keep data handling aligned with clinical and privacy regulations.
- Build search and statistics tooling so the team can locate datasets and pull summary stats quickly.
- Own data integrity across the full data lifecycle.
- University degree in Computer Science or related field.
- A minimum of 3 years of relevant working experience in a similar role and field.
- A minimum of 2 years of experience in the healthcare sector.
- Excellent verbal and written English communication skills.
- Strong analytical and problem-solving abilities.
- Ability to work independently and as part of a team.
- Strong Python skills, Rust ideally, R is a plus.
- Solid data engineering fundamentals: pipelines, file and format handling, validation, versioning.
- A high bar for correctness, reproducibility, and data integrity.
- Experience handling sensitive or regulated data, or the discipline to get up to speed quickly.
- Several years building and operating data tooling and infrastructure.
- Nice to have
- DICOM or medical imaging experience.
- Hands-on experience with DVC or similar data-versioning tools.
- Rust in production (deployed in a professional environment).
- Experience in regulated environments (medical, clinical, GDPR/PHI).
What We Offer
- A chance to be part of an exceptional team driving innovation in healthcare.
- A competitive salary in a supportive work environment that fosters work-life balance.
- Opportunities for professional growth and development in an international setting.
- A culture of collaboration and inclusion, which is fundamental to our ethos.
- Occasional travel to our HQ in Switzerland, immersing you in our core operations and company culture.
