Research Data Operations Engineer - Full Time - Hybrid

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.

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.
  
  

• Demonstrated entrepreneurial and collaborative mindset

• 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, R is a plus.
• Solid data engineering fundamentals: pipelines, file and format handling, validation, versioning.
• Experience running data infrastructure on self-managed servers and NAS-backed storage (we're not on the cloud).
• 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).