Research Data Operations Engineer

Retinai

. Create and support EHR extraction, matching and transformation tools.

Posted 10/9/2026full-timeMadrid • SpainMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data extraction, transformation, and integrity management within healthcare environments, utilizing strong Python and data engineering skills. Proficient in building and maintaining data pipelines, ensuring compliance with clinical and privacy regulations.

Highest-signal resume keywords

Python ProgrammingData Engineering FundamentalsDICOM ExperienceData Versioning with DVCHealthcare Sector Experience

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data ExtractionData TransformationData Integrity ManagementData Pipeline DevelopmentData ValidationFile and Format HandlingData AnnotationStatistical ToolingScriptingVersion Control

Soft Skills

Analytical SkillsProblem-SolvingCommunication SkillsTeam CollaborationIndependence

Tools & Technologies

DVCDICOMClinical Imaging DataEHR ExcerptsData Handling Tools

Certifications & Qualifications

University Degree in Computer Science

Industry Keywords

HealthcareClinical RegulationsGDPRPHIRegulated Environments

Tech Stack

Tools & technologies

PythonRust

About the role

Key responsibilities & impact

Create and support EHR extraction, matching and transformation tools.
Support data versioning with DVC, including updating, tracking, and rolling back datasets.
Build and maintain pipelines and tools to clean, validate, and organize clinical imaging data and EHR excerpts.
Support migration from a 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 statistics quickly.
Own data integrity across the full data lifecycle.
Write scripts, establish infrastructure, and own data integrity end to end.

Requirements

What you’ll need

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.
Nice to have: Hands-on experience with DVC or similar data-versioning tools.
Nice to have: Rust in production (deployed in a professional environment).
Nice to have: Experience in regulated environments (medical, clinical, GDPR/PHI).

Benefits

Comp & perks

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.