Cloud-Native Solutions for Climate & Geospatial Data
Design and implement ETL pipelines and virtualized datasets for TB to PB scale climate data. Optimize data flows for scientific computing, analysis, and ML training.
High-quality contributions across diverse open source projects, with specialized expertise in the Pangeo and Scientific Python ecosystem.
Practical guidance on modern open science workflows and cloud migration. Incremental solutions that respect academic realities while modernizing research practices.
Tailored talks, hands-on training, and workflow demonstrations. Build your team's expertise in modern climate data tools and best practices.
With 15 years of experience as a climate scientist and software engineer, I've dedicated my career to making climate and geospatial data more accessible through cloud-native technologies and open science. Having served as Senior Research Associate at Columbia University's Lamont-Doherty Earth Observatory, Manager for Data and Computing at LEAP, and Lead of Open Research at m2lines, I bring deep expertise in data engineering, distributed computing, and large-scale analytics for TB to PB scale climate datasets, leveraging tools like Python and Xarray to solve complex scientific data challenges.
As a longtime contributor to the Pangeo ecosystem and developer of open-source tools for climate research, I founded EarthStack to help research institutions, businesses, and the open science community build scalable data pipelines and efficient workflows for working with massive climate datasets. Whether you're looking to modernize your data infrastructure, contribute to open science, or unlock insights from CMIP and other large-scale datasets, I deliver proven solutions backed by deep technical expertise and a track record of successful implementations.
Interested in working together? Let's discuss how EarthStack can help with your project.