Data Engineer – 100%

Description du poste

This job ad was AI-translated from French. See original Job summary Hide Join HUG as a Data Engineer, contributing to digital transformation. Enjoy a collaborative and innovative work environment. Tasks Design and develop data processing solutions for migration. Integrate data from multiple sources while ensuring quality. Collaborate on national projects for interoperable health data. Skills Master's in Computer Science or equivalent; 2+ years experience. Proficiency in Python and SQL for data engineering. Experience with data orchestration tools like Airflow. About the job Full-time HUG contract type: Private law contract Department: Directorate of Digital Transformation and AI Company description With more than 13,000 employees representing 160 professions, the Geneva University Hospitals are a reference institution at the national and international level. To learn more about our institution, take a few minutes to discover the highlights of the year 2025 by clicking here. The Directorate of Digital Transformation and AI (DTN-AI) creates, integrates and manages all the IT applications of one of the most efficient hospital information systems to support the clinical and logistical activities of the Geneva University Hospitals. With a fleet of more than 12,500 workstations, 1,300 servers for over 250 applications serving all staff, available 24/7, the DTN-AI manages an HR information system for the 13,000 employees of the HUG and the 7 other Geneva institutions and a high-performance ERP for the most complex logistical and financial processes. The DTN-AI creates an integrated patient record at the cutting edge of the sector and contributes to the prominence of the HUG thanks to a recognised functional richness and close collaborations with all health professionals and their transversal management. Furthermore, the DTN-AI integrates state-of-the-art and everyday biomedical equipment as well as specialised applications for all medico-technical platforms. The mission of the DTN-AI is to support daily activities and build the future of a modern and efficient hospital, according to the strategic axes of the Institution relying on best practices and the most demanding standards. Job description As a Data Engineer, you design and develop data processing for data migration and creation of business datamarts. To carry out your tasks, you rely on technologies such as SQL, Python, MongoDB, as well as orchestration tools like Airflow. You join a team of 12 people and independently participate in a nationwide project aimed at breaking down the silos of medical data from the five Swiss university hospitals to create a national network of interoperable, secure health data dedicated to medical research. In this context, you exchange and participate in defining the common data format. You ensure the integration of data from multiple sources (databases, data warehouses, microservice APIs, Kafka streams), while guaranteeing their quality, consistency and integrity. In this respect, you implement monitoring mechanisms for data pipelines and ensure their performance, especially on large volumes. Your role also involves rigorous validation of data quality with business teams, setting up tools to facilitate data extraction and exploitation, as well as compliance with ethical, regulatory and data protection standards. Finally, thanks to your adaptability and autonomy, you successfully evolve in a dynamic and stimulating environment to carry out your projects. Qualifications You hold a Master’s degree in computer science or an equivalent diploma, and you have at least two years of professional experience as a Data Engineer, during which you have led end-to-end projects, ideally in high-volume data environments. Knowledge of the medical field or hospital information systems is a significant asset. Likewise, familiarity with medical data coding standards such as SNOMED, ATC or LOINC will be particularly appreciated in the context of the projects undertaken. You have strong skills in Python and SQL development applied to data engineering, as well as good mastery of relational and document databases, notably MongoDB. You also have significant experience with pipeline orchestration tools such as Airflow, as well as in setting up monitoring and optimisation mechanisms for data pipelines (DataOps), ensuring their performance and robustness. You understand microservices architectures and their impact on data flows, and you are comfortable with REST API integration as well as real-time data stream management via Kafka. Furthermore, you master good development practices, including CI/CD processes, and the use of collaborative tools such as Bitbucket and Jira. You possess excellent writing skills in French, enabling you to clearly document your work and synthesise complex information. You also have a good level of professional English. On the interpersonal level, you stand out for your ability to collaborate with members of the different teams within the DTN-AI and nationally within the project framework. You favour clear and constructive communication, promoting the exchange of best practices, mutual support and continuous improvement within the team. You adopt a rigorous and thoughtful approach that guarantees data quality while managing priorities professionally. When faced with challenges, you demonstrate autonomy in seeking information and favour a solution-oriented approach. You have a mindset ready to take on challenges in a demanding and complex environment. Additional information Start date: to be agreed Number of positions: 1 Activity rate: 100% Job class: 20 Contract: 12-month fixed-term, renewable Application deadline: 24.06.2026 Information request: Mr V. Rejany, Team Leader "Data – Self-service Data Foundation", Vincent.Rejany@hug.ch Your application file must include a letter demonstrating your motivation, your curriculum vitae, copies of diplomas and certificates required for the position and the last 2 work certificates. This announcement is addressed equally to women and men. Wishing to engage in the fight against unemployment, the HUG encourage applications coming from the Cantonal Employment Office. Only applications submitted via the recruitment platform will be considered. Paper and email applications will not be processed.