Retinai
Retinai
Retinai is a healthcare AI and data management company that helps life sciences organizations, clinics, and researchers turn complex medical data into actionable insight. Its Discovery platform supports real-world evidence, precision medicine, clinical research, and collaboration across ophthalmology, neurodegenerative, vascular, and rare disease programs. Retinai provides tools for AI-assisted data analysis, clinical trial workflows, patient management, and secure cloud-based data sharing, including CE-marked models designed to support research and care teams.

Research Data Operations Engineer — Retinai, Madrid Hybrid

Manage data pipelines, governance, and integrity for Retinai’s healthcare AI and clinical imaging systems. The role covers EHR tooling, DVC dataset versioning, DICOM migration, and regulated data access.

Description

  • Develop and maintain tools for extracting, matching, and transforming EHR data.
  • Manage dataset updates, tracking, and rollbacks with DVC.
  • Build pipelines and tooling to clean, validate, and organize clinical imaging data and EHR excerpts.
  • Help migrate data from a custom image format to DICOM.
  • Improve the speed and usability of research data annotation.
  • Configure and administer access controls for appropriate data access.
  • Ensure data practices comply with clinical and privacy regulations.
  • Develop search and statistical tools for locating datasets and retrieving summary statistics efficiently.
  • Maintain data integrity throughout the complete data lifecycle.
  • Create scripts, establish infrastructure, and take end-to-end ownership of data integrity.

Requirements

  • University degree in Computer Science or a related discipline.
  • At least three years of relevant experience in a comparable role and field.
  • At least two years of professional experience in healthcare.
  • Excellent spoken and written English communication skills.
  • Strong analytical thinking and problem-solving skills.
  • Comfort working independently and collaboratively within a team.
  • Strong Python proficiency; Rust is preferred, and R is an advantage.
  • Solid data engineering knowledge covering pipelines, file and format handling, validation, and versioning.
  • High standards for correctness, reproducibility, and data integrity.
  • Experience working with sensitive or regulated data, or the ability to learn these practices quickly.
  • Several years of experience building and operating data tools and infrastructure.
  • DICOM or medical imaging experience is desirable.
  • Practical experience with DVC or comparable data-versioning tools is desirable.
  • Professional production experience with Rust is desirable.
  • Experience in regulated medical, clinical, GDPR, or PHI environments is desirable.

Benefits

  • Join a team focused on advancing healthcare innovation.
  • Receive a competitive salary in a supportive environment designed to encourage work-life balance.
  • Pursue professional growth and development in an international workplace.
  • Work in a collaborative and inclusive culture that is central to the company’s values.
  • Travel occasionally to the headquarters in Switzerland to engage with core operations and company culture.

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