Join a project-based engineering team in Zürich, where you help turn research ideas and prototypes into real, reusable data science systems. Work at the intersection of research and engineering, supporting projects in health, climate, energy, digital society, and large-scale data ecosystems. You will make sure solutions are not only FAIR but also usable, scalable, and sustainable for real-world needs.
Start date: June 1, 2026 (negotiable).
Deine Aufgaben
- Transform early-stage research ideas and prototypes into production-ready systems.
- Engage in exploration and prototyping during early project phases, shaping solutions and testing approaches.
- Develop Minimum Viable Products (MVPs) with operational, reusable components for production environments.
- Collaborate with engineers across the stack, focusing on backend, data, and infrastructure, and support lightweight user-facing elements when needed.
- Ensure successful transition of MVPs into production by working closely with platform teams and partner IT units.
- Co-design solutions with users and domain experts, participate in workshops, and refine requirements into robust implementations.
- Follow best practices in engineering and data, focusing on reproducibility, maintainability, interoperability, and production readiness.
Was du mitbringst
- Background in software engineering, data engineering, or a related field.
- Solid foundation in software or data engineering, typically with a Master’s degree or higher (e.g. PhD) in Computer Science or a related field, or equivalent professional experience.
- Comfortable working between teams, bridging research, engineering, and operations.
- Experience with modern software and data engineering practices such as version control, testing, APIs, data pipelines, containerisation, reproducible workflows (e.g. Docker, CI/CD, Nix), and programming in languages like Python, Go, Rust, or similar.
- Interest in data-intensive systems.
- Experience in application domains (health, climate, energy, etc.) is a plus but not required.
- Exposure to data modelling or semantic interoperability (e.g. ontologies, common data models) is a plus.
- Attitude, curiosity, and a drive to learn are highly valued; technical skills can be developed on the job.
- Enjoy building practical systems, navigating ambiguity, engaging with stakeholders, and iterating towards solutions.
- Care about quality, clarity, long-term usability, and building secure systems aligned with best practices.
Was wir dir bieten
- Work in a stimulating, collaborative, and cross-disciplinary environment at a world-class research institution.
- Flexible work arrangements.
- Exciting challenges and varied projects with room to learn and grow.
- Opportunity to use your skills to make an impact on research communities and society.
- Freedom to experiment and learn new technologies.
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Über uns
The Swiss Data Science Center (SDSC) is a national research infrastructure in data science and AI, founded by EPFL and ETH Zurich. SDSC supports academic labs, hospitals, industry, and public sector partners through their data science journey, offering expertise across health, energy, climate, and more. With multidisciplinary teams in Lausanne, Zurich, and Villigen, SDSC drives impactful projects and innovation in data science.
Das Team
The engineering team in Zürich works closely with researchers and platform teams, focusing on turning research into practical, production-ready solutions. The team values collaboration, creativity, and continuous learning, supporting each other to solve real-world challenges across a variety of domains.