Software Research & Development Engineer

80%-100%, Zurich, fixed-term

The Swiss Data Science Center (SDSC) is a national research infrastructure specializing in data science and artificial intelligence (AI) within the ETH domain, established by founding partners ETH Zurich and EPFL. Our mission is to support academic labs, hospitals, industries, and public sector stakeholders through their entire data science journey, from data collection and management to machine learning, AI, and industrialization. With a large multidisciplinary team of professionals located in Lausanne, Zurich, and Villigen, the SDSC offers expertise and services across various domains, including health and biomedical sciences, energy and sustainability, climate and environment, and large-scale scientific infrastructures.

Project Background

The SDSC is seeking a Software Research & Development Engineer to join its project-based engineering team in Zürich. This team is dedicated to transforming research outcomes into production-ready data science infrastructure, complementing platform teams by exploring, building, and validating solutions prior to their sustainability as services.

In this role, you will work at the intersection of research and engineering, taking early-stage ideas, prototypes, and emerging solutions and converting them into reusable systems prepared for real-world deployment. You will align with FAIR principles while ensuring that the solutions are also usable, scalable, and sustainable in practice.

Projects will address specific needs across domains like health and biomedical sciences, climate and environment, energy and sustainability, digital society, and large-scale data ecosystems.

Job Description

• Contribute to projects evolving through two complementary modes.
• Engage in focused exploration and prototyping in early phases, shaping solution spaces, testing approaches, and making technical decisions.
• Contribute to Minimum Viable Product (MVP) development as projects mature, building operational, reusable components suitable for production environments.
• Collaborate with engineers across the stack to build end-to-end solutions, primarily focusing on backend, data, and infrastructure components, while occasionally supporting lightweight user-facing elements.
• Ensure continuity beyond the project lifecycle by collaborating closely with internal platform teams and partner IT units to transition successful MVPs into production environments.
• Co-design solutions with users and domain experts, participate in collaborative workshops, and iteratively refine requirements into robust implementations.
• Follow established engineering and data best practices, emphasizing reproducibility, maintainability, interoperability, and production readiness.

Profile

• We welcome candidates with varied experience levels; what matters most is your approach to problem-solving and collaboration.
• You enjoy building practical systems and are comfortable navigating ambiguity, engaging with stakeholders, and iterating towards solutions.
• You prioritize quality, clarity, long-term usability, and building systems that are secure by design and aligned with best practices.
• A background in software engineering, data engineering, or a related field, along with an interest in data-intensive systems, is essential.
• You should have a solid foundation in software or data engineering, typically gained through a Master’s degree or higher (e.g., PhD) in Computer Science or a related field, or equivalent professional experience. Experience in relevant application domains is a plus but not required.
• You must be comfortable working at the interface between teams, bridging research, engineering, and operations to ensure successful adoption and sustainability of created solutions.
• Experience with modern software and data engineering practices such as version control, testing, APIs, data pipelines, containerization, and reproducible workflows (e.g., Docker, CI/CD, Nix), as well as programming in languages like Python, Go, Rust, or similar, is beneficial.
• Exposure to data modeling or semantic interoperability (e.g., ontologies, common data models) is considered a plus.
• During your development, we value your attitude, curiosity, and willingness to learn; technical skills can be cultivated on the job.

Workplace

Join us in a stimulating, collaborative, cross-disciplinary environment within a world-class research institution. We offer flexible work arrangements and exciting challenges, varied projects, and ample opportunities for learning and growth. You'll have the chance to follow your passion and make a meaningful impact on research communities and society while experimenting with and learning new technologies.

We Value Diversity and Sustainability

In alignment with our values, ETH Zurich promotes an inclusive culture. We uphold equality of opportunity, value diversity, and nurture a working and learning environment that respects the rights and dignity of all our staff and students. Visit our Equal Opportunities and Diversity website to learn more about how we ensure a fair and open environment for everyone. Sustainability is a core value for us as we strive for a climate-neutral future.

Curious? So Are We.

To explore this opportunity further, please apply online using the form below. Only applications matching the job profile will be considered.

For further information about the SDSC, please visit our website. For questions regarding the position, contact Oksana Riba Grognuz at oksana.riba@epfl.ch. Please note that we do not accept applications via email or postal services.

About ETH Zürich

ETH Zurich stands as one of the world’s leading universities specializing in science and technology. Renowned for our excellent education, cutting-edge research, and direct knowledge transfer to society, we host over 30,000 individuals from more than 120 countries, fostering an environment that promotes independent thinking and inspires excellence. Positioned in the heart of Europe, we collaborate globally to develop innovative solutions for today’s and tomorrow’s challenges.