Data Engineer

Who We Are

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.

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.

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.

The Way We Work

The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice:

Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping.

Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through.

Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together.

Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work.

Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most.

Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact.

About the Role

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 Data Engineer , you will help us get there.

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.

What You’ll Do

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

Build and maintain the clean, documented tables that analysts and data scientists actually work from — not raw dumps

Own data quality end-to-end: schema management, freshness monitoring, lineage tracking, and alerting when something breaks

Partner with engineering and GTM teams to instrument what isn't already tracked

Work closely with product, infra, and ML teams, primarily unblocking them

What You’ll Need

10+ years of total experience in analytics engineering, data engineering, or similar data-focused roles

Deep expertise in data modeling, ETL pipelines, and data warehouse architecture

Strong technical foundation with expertise in SQL, Python, and modern data stack tools (dbt, SQLMesh, etc)

Experience partnering with Data Science, Product, and Engineering leaders to deliver key product metrics and user behavior insights

Demonstrated ability to balance strategic thinking with hands-on technical leadership

Strong communication skills with the ability to translate complex technical concepts for diverse audiences

Experience scaling analytics functions from early stage to maturity in rapidly changing environments

Track record of establishing data governance, quality standards, and best practices

A bias for action and urgency, not letting perfect be the enemy of the eff …