Data Engineer

XUND is a leading digital health scale-up that enables healthcare companies to digitize patient interactions and translate data into actionable insights.

It's our vision to empower patients to make better decisions. But we cannot do it alone: we need leaders, doers, and innovative minds to turn our vision into reality.

That is why we are looking for an ambitious, highly committed, and entrepreneurial team player who shares our values of putting patients first, building an inspiring and open environment and challenging the status quo.

The Role

Join our team as a Senior Data Engineer and architect our company's new data backbone from the ground up. Your expertise in clinical ontologies and data modeling will turn messy, large-scale healthcare data into a unified, high-performing knowledge graph. You will work directly with medical experts, product teams and data scientists to translate complex clinical domain logic into clean, interconnected data structures & models that bring real value to patients and practicing doctors.

Your Responsibilities

• Find creative uses of different database types and data pipelines to ensure patient data we collect and medical knowledge we produce stay consistent & interoperable.

• Develop and integrate parts of our clinical inference engine relying both on rule-based and statistical models.

• Design and extend clinical data models using domain ontologies (e.g., SNOMED-CT, FHIR, UMLS) to turn healthcare data into rich, queryable graph structures.

• Translate research insights into scalable, production-grade software efficiently in an agile and close-knit team.

• Work closely with medical experts to capture clinical workflows and validate ontology mappings.

• Shape the technical direction, schema design, and engineering best practices across the engineering team.

Your Profile

• MSc or PhD in computer science, mathematics, or related field.

• +4 years of proven industry experience in working with medical data or in data engineering (or appropriate academic research).

• Strong knowledge of graph databases, query languages, search algorithms and/or inference systems (e.g. Neo4j, Memgraph, Cypher, SQL, Datalog).

• Extensive experience in software development with Python and/or TypeScript – being comfortable with switching languages/frameworks.