Software Research & Development Engineer
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 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)
* 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
* Open to candidates at all experience levels – we value a problem‑solving mindset and a collaborative spirit.
* You enjoy building systems that work in practice, not just in theory.
* You care about quality, clarity, long‑term usability, and secure, best‑practice‑aligned solutions.
* Likely have a background in software engineering, data engineering, or a related field, and an interest in data‑intensive systems.
* 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.
* Comfortable working at the interface 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 such as Python, Go, Rust, or similar.
* Exposure to data modelling or semantic interoperability (e.g. ontologies, common data models) is a plus.
* No need to know every technology used – willingness to learn is valued.
Workplace
Location: Zürich, Switzerland.
We offer
* A stimulating, collaborative, cross‑disciplinary environment in a world‑class research institution.
* 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.
Equal Opportunities
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. Sustainability is a core value; we are consistently working towards a climate‑neutral future.
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