Data Engineer

Gridmatic is a high-growth startup and a new kind of energy company, delivering affordable, clean power by optimizing renewable energy and grid-scale batteries. With offices in the Bay Area and Houston, we bring together Silicon Valley–style innovation with deep, hands-on expertise in real-world power markets and energy retail. As solar and wind become the fastest-growing sources of electricity, variability from weather and grid conditions makes energy prices more volatile. Gridmatic tackles this challenge with industry-leading forecasting and optimization—and gives our team the opportunity to work on problems that truly matter. Forecasting and trading energy are the foundation of what we do. We ingest large-scale data—weather, prices, load, and grid conditions—to build probabilistic machine learning forecasts that drive real operational decisions. Our work directly determines when power is bought, stored, or deployed, turning uncertainty into value for customers and the grid. Our impact is measurable. Gridmatic is the most profitable participant in ERCOT’s wholesale market and operates the top-performing battery asset in CAISO. Profitable without venture capital, we offer a collaborative, low-ego environment where rigorous thinking, autonomy, and continuous learning are core to how we work. The role We’re looking to hire our first data engineer at Gridmatic! Looking for a startup-minded engineer who works closely with our ML and optimization teams to ingest and transform the data critical to all the work we do. We use a lot of interesting, real-world data - large-scale weather forecasts, timeseries data from the grid and energy markets, and telemetry from physical batteries. We’re looking for someone who’d be able to take ownership of this area to make sure the data is ingested and transformed reliably.