Medior Data Engineer

Let's transform healthcare

About Vitestro

Founded in 2017 in Utrecht, Vitestro is pioneering the future of blood collection with the Aletta® Autonomous Robotic Phlebotomy Device™ (ARPD™). This groundbreaking medical device combines advanced multi-modal imaging (near-infrared, ultrasound, and Doppler ultrasound) with robotics and AI to perform the entire diagnostic blood draw procedure autonomously.

By addressing critical healthcare staffing shortages and improving patient experience, Vitestro is transforming one of the most common and essential medical procedures. With more than 90 team members growing rapidly, we are scaling our impact. As we placed our first devices with customers, we are now expanding our team to ensure successful implementation and long-term reliability.

At Vitestro, we are committed to continuous innovation and improvement.

Join us as our new Data Engineer.

As a Data Engineer in the Application Team at Vitestro, you will play a critical role in enabling us to make data-driven decisions and gain deep insights into the performance of our devices. With our team at a pivotal phase of growth, it’s the perfect time for dynamic individuals like you to contribute and make an impact.

Your Responsibilities

In an agile, cloud-native environment, you will:

• Develop, enhance, and maintain scalable ETL/ELT (batch) data pipelines using Python (Polars) scripts in containerized deployments, including writing unit tests, managing schema versioning, and performing impact analyses.

• Integrate pipelines using cloud-native orchestration and execution services.

• Analyze and resolve data issues, coordinating required changes with software engineers and extending automated data quality checks (e.g. completeness and consistency).

• Collaborate closely with the Senior Data Engineer to scale pipeline performance while adhering to established architectural patterns.

• Partner with engineering and business stakeholders to understand data requirements and deliver clean, well-structured, and insightful dashboards.

• Contribute to pipeline auditability, traceability, and controlled change management.

You will also have opportunities to grow beyond business intelligence by contributing to data science initiatives, fault analysis tools, and support for machine learning and AI workflows embedded in our devices.