About us:
The RWTH Aachen University Hospital combines medical care, teaching and research at an international standard. The University Clinic covers the entire spectrum of medicine, with 37 specialist clinics, 35 institutes and six interdisciplinary units. Integrating health care, research and teaching in one central building, this hospital provides optimal conditions for intensive interdisciplinary exchange and collaboration, as well as for clinical and scientific networking. Outstandingly well-qualified teams of doctors, nurses and scientists competently care for the health of patients. Patient-centered medicine and follow-up care at high quality standards is ensured by the approximately 9,000 staff. With 1,400 beds, the University Clinic cares for around 50,000 inpatient and 200,000 outpatient cases per year.
The department for Anesthesiology is looking for a
Data Engineer (f/m/d)
Working hours: Full-time 100% (currently 38,5 hours/week)
Duration/Term of employment: 3 years with option of prolongation. The successful candidate is expected to pursue a doctoral degree
Start date: as soon as possible
Remuneration/Rates: EG 13 (TV-L) The main task is to support the collection, storage and processing of large biomedical datasets by designing, building and maintaining a high-performance infrastructure and architecture for data processing systems and developing data pipelines to make the data accessible for analysis and applications.
Design, build and maintain the infrastructure and architecture for a unified data processing system
Develop and maintain data pipelines to read structured and unstructured medical data (such as biosignals and clinical data) to enable evaluation using biostatistics and machine learning
Collaboration with colleagues from medical teams, natural sciences, medical informatics, biostatistics and data science, as well as the Data Integration Center at the University Hospital Aachen and industry partners
Create APIs for data access and implement user-friendly applications step by step
Improve and ensure data quality by implementing data standards,anomaly detection schemes and data deduplication strategies
Support data analysis and machine learning model development by cleaning and preparing data for analysis
Master's degree in Computer Science, Data Science, Medical Infromatics, Biomedical Engineering, Applied Mathematics, Natural Sciences, or other relevant fields that gives you good skills to design, build and maintain data processing systems and develop scalable data pipelines for analyzing data
Strong practical and theoretical knowledge in: Database design and management (relational, NoSQL, time-series, and multimodal databases), Data integration and ETL processes and API development for data access
Practical experience with revelant programming languages such as SQL, Phython, or Java
Eperience with Big Data technologies (e.g. Apache Hadoop, Spark, Kafka, Airflow)
Knowledge or experience with data flows and data architectures in the medical field as well as knowledge of common data formats, standards and protocols in the heathcare sector
Desirable:
Experience with HPC clusters and cloud platforms (AWS, Azure, GCP)
Experience in effective project and time management, for example working in Agile/Scrum environments
Knowledge in the field of artificial intelligence or machine learning and their application in biomedical data science
Knowledge of version control with Git and GitLab as well as Docker and containerization techniques
Experience in UX/UI design
Team player with the ability to communicate complex analytical and technical concepts to non-experts
highly organized, proactive and decisive in managing work tasks
Problem-solving and critical thinking skills
Fluent in English (C1 level) and good German skills (B1 level)
Willingness to learn new data tools, frameworks and industry trends
We offer…
30 days of vacation per year for full-time employment
A bonus of 3,000 euros for employees who help recruit employees in the care sector
An attractive company pension scheme from VBL
Education opportunities, including updating and upgrading
Access to public transport
In-house kindergarten (places subject to availability)
Staff residences (places subject to availability and by arrangement)
An onboarding app for new employees
Extended opening hours in the staff restaurant