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The Data Integration Center (DIZ) is looking for the next possible date for a
System administrator (m/f/d)
As a central institution, the Data Integration Center (DIZ) represents a basic component for data-driven medicine at the University Medical Center Freiburg (UKF) and is part of the nationwide Medical Informatics Initiative (MII) and the Network University Medicine (NUM).
The aim is to process patient care data in a standardized manner, while maintaining data protection, and to make it available for quality assurance tasks, process optimization and, in particular, for scientific questions. In this way, the DIZ makes a significant contribution to improving patient care and scientific progress.
We offer you the opportunity to work as a system administrator in a dynamic environment. You will work closely with our Data Engineers and Data Scientists and use state-of-the-art technologies to realize groundbreaking projects in the field of data management, business intelligence and big data.
Become part of our dedicated team and play a key role in shaping the future of data-driven medicine at UKF.
We offer you:
- a job in one of the most exciting and up-to-date areas of healthcare
- Flexible working time models
- Modern IT equipment that enables you to work on the move
- a workplace in a renowned university hospital at the cutting edge of technology
- a performance-related salary
- a family-friendly workplace and childcare facilities
- attractive benefits: company pension scheme and capital-forming benefits, UKF job ticket, sports and health offers (Unifit, Hansefit), “corporate benefits” bonus program and other standard hospital benefits
- Professional development through internal and external training courses
As part of a committed and collegial team, you will use your skills for the following tasks in particular:
- Server operation as well as the introduction and integration of new tools and technologies to optimize our IT infrastructure (monitoring, IAM tools, etc.)
- Collaboration on the further development of the DIZ system architecture
- Automation of processes using scripts (e.g. Ansible, Bash, Python)
- Operation and ongoing implementation of technical components from the MII and NUM networks
- Connection of the protected data room to the backend structures / data warehouse
- Collaboration on the further development of the DIZ service spectrum, e.g. a scientific workstation or protected data room (based on R-Studio, Jupyter Notebook, etc.)
You bring with you:
- A degree in (bio/medical/business) computer science, a degree in IT for system integration or equivalent professional experience in the field of computer science or data science
- Experience in the productive operation of IT applications on Linux systems
- Programming skills (e.g. in Java or Python) in the context of data integration or server automation
- Knowledge of and experience with modern operating, development and integration methods (e.g. Docker, “Infrastructure as Code”, DevOps)
- Ideally experience with common data analysis tools and technologies (such as R-Studio, Numpy or similar) and data processing tools (e.g. Apache Kafka)
- Prior knowledge of clinical information processing (e.g. HIS, HL7, FHIR), clinical workflows and interoperability standards in healthcare (e.g. LOINC, SNOMED-CT) would be desirable
- A reliable, structured and goal-oriented way of working
- Very good written and spoken communication skills
The position is initially limited until 31.12.2026.
Are you interested? Then send us your detailed application by 30.06.2024 via our online portal.
University Medical Center Freiburg
Data Integration Center
Dr. Julius Wehrle
Georges-Köhler-Allee 302, 79110 Freiburg
Do you have any questions? Then give us a call or send us an e-mail:
0761/270-22370
General information: Remuneration is based on the pay scale. Full-time positions are generally divisible, provided there are no official or legal reasons to the contrary. Severely disabled applicants will be given special consideration if equally qualified. Recruitment is carried out by the Human Resources department.
Data Science Python Data Engineering Apache Kafka hl7 Linux DevOps hl7-fhir System administration snomed-ct Docker NumPy Java