Earth Systems Data Manager / Earth Systems Data Manageress

Job Opportunity: Earth Systems Data Manager

The Center for Climate Systems Modeling (C2SM) at ETH Zurich is a joint, interdisciplinary center that connects ETH Zurich with partner institutions. It serves as a technology and networking platform to support the development and application of Earth system, weather, and climate modeling, data infrastructure, and impact research. This position will involve close collaboration with the Swiss National Supercomputing Centre (CSCS).

With the ever-increasing volume and diversity of Earth observations collected from satellites, airborne instruments, and in-situ measurement networks, effectively harnessing these data is crucial for advancing our understanding of the Earth system.

To tackle this challenge, a robust data management framework is being developed to make rapidly growing Earth-system datasets accessible and usable for the scientific community. The Earth Systems Data Manager will play a pivotal role in shaping this framework by:

• Identifying and evaluating Earth system observations relevant to interdisciplinary research needs.
• Curating data collections by assessing quality, completeness, and scientific value.
• Creating comprehensive metadata and documentation to support data discovery and use.
• Beginning the development of a web-based platform to provide users with an overview of the available data.
• Coordinating with researchers in climate science, environmental monitoring, data science, and related fields.
• Collaborating with a dynamic and international team of researchers and developers to operate and further advance the research platform.
• Supporting interdisciplinary research projects that require multiple data sources.
• Working with high-performance computing platforms for data storage and analysis.

Qualifications

• Degree in Earth sciences, data science, computer science, or a related field.
• Knowledge of satellite data formats and remote sensing.
• Experience with large datasets (petabyte-scale), data management, and data quality control.
• Proficiency in programming languages such as Python, R, or Julia, and experience with scientific data libraries (e.g., xarray, netCDF4, HDF5, Zarr), as well as workflow automation on HPC systems.
• Strong communication skills for effectively collaborating across different scientific disciplines.

Beneficial Skills

• Experience working in an interdisciplinary environment.
• PhD in remote sensing or a related field.
• Experience leading projects across diverse domains.
• Knowledge of user support, data documentation, and FAIR data principles (Findable, Accessible, Interoperable, Reusable).

In this role, you will be at the forefront of Earth system modeling, high-performance computing, and data-driven science. You will join the C2SM, a vibrant and interdisciplinary community that connects weather and climate researchers, computational scientists, and data experts across ETH Zurich and its partner institutions. This position provides an opportunity to shape modern data infrastructure for the Swiss climate and weather research community, contribute to impactful scientific projects, and support researchers working with rapidly growing environmental datasets. You will benefit from excellent technical resources, access to state-of-the-art HPC systems, strong mentorship, and opportunities for professional development in a collaborative and forward-looking research ecosystem.

The position is initially limited to two years, with the possibility of extension.

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

For further information about C2SM, please visit our website. For specific inquiries, you may contact Dr. Christina Schnadt Poberaj at phone no. +41 44 633 8458 or via email at christina.schnadt@c2sm.ethz.ch, or Prof. Andreas Prein at phone no. +41 44 63 23029 or via email at andreas.prein@env.ethz.ch.

Please note that the pre-selection is conducted by responsible recruiters and not through artificial intelligence.