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GridCARE is seeking a Data Engineer to design robust data ingestion pipelines in cloud environments, integrate new datasets, and analyze time-series and non-relational data to derive actionable insights. You will collaborate with UI/UX and AI leads to leverage data for innovative solutions.
This is a unique role combining deep data engineering and cutting-edge AI, applied to accelerate power access in the energy industry.
GridCARE solves data center developers' most urgent bottleneck - immediate access to power - through a pioneering physics-based generative AI platform that unlocks gigawatts of near-term capacity from today's grid. Partnering with utilities, GridCARE applies a proprietary playbook to create additional network capacity on existing transmission infrastructure without costly upgrades or multi-year delays. Founded at Stanford's Doerr School and backed by leading investors in Energy and AI, GridCARE is working with major technology and data center companies to accelerate interconnection requests for large-load and data center projects.
As a fast-growing startup, we are seeking a skilled Data Engineer to help develop data-driven solutions that have real-world impact.
We are looking for a Data Engineer with hands-on experience in data ingestion into cloud environments, finding and retrieving new datasets, and performing analysis on various data types, including time-series and non-relational data. In this role, you'll streamline data processes, ensure data quality and accessibility, and collaborate with UI/UX and AI leads to leverage data for innovative solutions.
This is a unique opportunity to combine deep data engineering and scientific expertise with cutting-edge AI solutions applied to solve the most impactful speed-to-power in the energy industry.
Join us in tackling one of the most important infrastructure challenges of our time — enabling the energy foundation for the age of AI.
About the company
GridCARE