Data Engineer

<div class="content-intro"><h2><strong>Who We Are</strong></h2> <p>Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.</p> <p>Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.</p> <p>We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.</p> <div class="c-message_actions__container c-message__actions">&nbsp;</div></div><h2><strong>What We're Looking For</strong></h2> <p>We're moving fast, and our data infrastructure needs to keep up. GPU telemetry, product usage, and operational signals are accumulating faster than our pipelines can surface them. We're at the stage where the right data foundation unlocks everything: better product decisions, faster model iteration, and cleaner ops. As our first<strong> Data Engineer</strong>, you will help us get there.</p> <p>This is an early, high-scope role reporting to our VP of Product. You'll own data reliability across the company: clean tables, documented lineage, and signal flowing to where it's needed. You drive projects from conception to production without waiting to be told what to do next.</p> <h2><strong>What You’ll Do</strong></h2> <ul> <li>Design and own ETL/ELT pipelines that move GPU telemetry, product usage, operational data, and customer data from where it lives to where it's useful</li> <li>Build and maintain the clean, documented tables that analysts and data scientists actually work from — not raw dumps</li> <li>Own data