3–6+ years of experience in a data engineering or analytics engineering role, ideally at a high-growth startup or in a domain involving complex, real-time data (energy, fintech, marketplace, or similar).
Strong dbt fundamentals — you know how to design models that are maintainable, not just functional. You think about testing, documentation, and downstream consumers as part of the job, not afterthoughts. Solid SQL is a given; Python for pipeline development or data quality tooling is a plus.
Hands-on experience with Snowflake, including schema design, query performance, and understanding the cost/performance tradeoffs of how data is structured and accessed. Comfort with GCP data services (BigQuery, Cloud Storage, Pub/Sub) is a plus given our infrastructure footprint.
Experience building dashboards for business stakeholders in tools like Hex, Looker, or similar. You know the difference between a dashboard that gets used and one that doesn’t.
Energy markets or regulated industry experience is not required, but genuine curiosity about how electricity pricing, competitive markets, and the grid work will make this role more interesting to you.
An AI-native approach to your own productivity — you’re actively using AI tools to accelerate development and aren’t waiting for someone to tell you to start.