Senior Data Engineer — Knowledge Graphs (Clinical)

XUND; Wien; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Benefits dieser Stelle

Training budget

VSOPs program

Office dogs

Remote work

Zusammenfassung

XUND is seeking a Senior Data Engineer to architect a new data backbone. You will transform messy healthcare data into a unified knowledge graph, collaborating with medical experts, product teams and data scientists to translate complex clinical logic into clean, interconnected data models.

You will design clinical data models using SNOMED-CT, FHIR and UMLS, build scalable pipelines, and contribute to the inference engine with rule-based and statistical approaches within an agile team.

Qualifikationen

• MSc or PhD in computer science, mathematics, or related field.
• +4 years of proven industry experience with medical data or data engineering.
• Strong knowledge of graph databases, query languages, search algorithms and/or inference systems (Neo4j, Memgraph, Cypher, SQL, Datalog).
• Extensive experience in software development with Python and/or TypeScript.

Aufgaben

• Find creative uses of different database types and data pipelines to ensure patient data and medical knowledge stay consistent and interoperable.
• Develop and integrate parts of our clinical inference engine using rule-based and statistical models.
• Design and extend clinical data models using domain ontologies (e.g., SNOMED-CT, FHIR, UMLS).
• Translate research insights into scalable, production-grade software in an agile team.
• Collaborate with medical experts to capture clinical workflows and validate ontology mappings.
• Shape the technical direction, schema design, and engineering best practices across the team.

Kenntnisse

Graph databases

Cypher/Query languages

Python/TypeScript

Medical data experience

EU work permit

Ausbildung

MSc/PhD in CS or Math

Tools

Neo4j

Memgraph

SQL

FHIR

Jobbeschreibung

XUND is seeking a Senior Data Engineer to architect a new data backbone. You will transform messy healthcare data into a unified knowledge graph, collaborating with medical experts, product teams and data scientists to translate complex clinical logic into clean, interconnected data models.

You will design clinical data models using SNOMED-CT, FHIR and UMLS, build scalable pipelines, and contribute to the inference engine with rule-based and statistical approaches within an agile team.