The
Swiss Data Science Center (SDSC) is a national research infrastructure in data science and artificial intelligence (AI) of the ETH domain, with EPFL and ETH Zurich as founding partners. Its mission is to support academic labs, hospitals, industry and public sector stakeholders, including cantonal and federal administrations, through their entire data science journey, from the collection and management of data to machine learning, AI, and industrialization. With a large multidisciplinary team of professionals across three locations (Lausanne, Zurich, Villigen), the SDSC provides expertise and services to various domains, such as health and biomedical sciences, energy and sustainability, climate and environment, and large-scale scientific infrastructures.
Project background The Swiss Data Science Center (SDSC) is hiring a Software Research & Development Engineer to join its project-based engineering team in Zürich. This team focuses on transforming research outcomes into production-ready data science infrastructure. It operates in a complementary role to platform teams: exploring, building, and validating solutions before they are adopted as sustainable services.
You will work at the intersection of research and engineering, taking early-stage ideas, prototypes, and emerging solutions, and turning them into reusable systems ready for real-world deployment. This includes aligning with FAIR principles while going further: ensuring that what is FAIR is also usable, scalable, and sustainable in practice.
Projects are driven by concrete needs across domains such as health and biomedical sciences, climate and environment, energy and sustainability, digital society, and large-scale data ecosystems.
Start of position: June 1, 2026 (negotiable)
Job description - You will contribute to projects that evolve through two complementary modes.
- In early phases, you will engage in focused exploration and prototyping, shaping solution spaces, testing approaches, and making technical choices.
- As projects mature, you will contribute to Minimum Viable Product (MVP) development, building operational, reusable components that can transition into production environments.
- You will collaborate with engineers across the stack to build end-to-end solutions, contributing primarily to backend, data, and infrastructure components, while occasionally supporting lightweight user-facing elements where needed.
- A key part of the role is to ensure continuity beyond the project lifecycle. You will work closely with internal platform teams and partner IT units to transition successful MVPs into production, ensuring they are maintainable, transferable, and ready for operational use.
- Across all phases, you will co-design solutions with users and domain experts, participate in collaborative workshops, and iteratively refine requirements into robust implementations.
- Our work follows established engineering and data best practices, with a strong focus on reproducibility, maintainability, interoperability, and production readiness:
Profile - We are open to candidates across different levels of experience. You may be early in your career or already experienced; what matters most is your approach to problem-solving and collaboration.
- You enjoy building systems that work in practice, not just in theory. You are comfortable navigating ambiguity, engaging with stakeholders, and iterating towards solutions.
- You care about quality, clarity, long-term usability, and building systems that are secure by design and aligned with best practices.
- You likely have a background in software engineering, data engineering, or a related field, and an interest in data-intensive systems.
- You bring a solid foundation in software or data engineering, typically developed through a Master's degree or higher (e.g. PhD) in Computer Science or a related field, or equivalent professional experience. Experience in one of the application domains is a plus, but not required.
- Importantly, you are comfortable working at the interface between teams, helping bridge research, engineering, and operations, and ensuring that what is built can be successfully adopted and sustained.
- You may have 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 such as Python, Go, Rust, or similar.
- Exposure to data modelling or semantic interoperability (e.g. ontologies, common data models) is a plus.
- We do not expect you to know every technology we use. We value attitude, curiosity, and a drive to learn, technical skills can be developed on the job.
We offer - A stimulating, collaborative, cross-disciplinary environment in a world-class research institution;
- Flexible work arrangements;
- Exciting challenges, varied projects, and plenty of room to learn and grow;
- An opportunity to follow your passion and use your skills to make an impact on research communities and society;
- A possibility to spark your creativity by experimenting and learning new technologies;
> Working, teaching and research at ETH Zurich We value diversity and sustainability In line with
our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our
Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us - we are consistently working towards a
climate-neutral future.
