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Founding Data Engineer

Gridmatic Inc · gridmatic.com
San FranciscoHybrid
Apply on Gridmatic Inc’s site
Posted 2 months ago. 463 more Data Engineer jobs in the United States went up on company career pages this week. See the newer ones

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The job in short

A hybrid Data Engineer role at Gridmatic Inc in San Francisco. Skills mentioned: Python, SQL, Airflow, dbt, Insurance.

PythonSQLAirflowdbtInsurance

Details

Found
39 d ago · posted 2026-08-13
Location
Cupertino, San Francisco
Pay (as listed)
$180,000–$220,000 a year

Full description

The role Gridmatic trades power, runs battery storage, buys renewable supply and sells electricity to retail customers. Each of these businesses produces messy data: exchange and broker statements, grid settlements, meter reads and invoices. We need to turn these into numbers people trust: what our positions are worth, what we earned and what we're owed. We’re looking for a startup-minded engineer to join as our first data engineering hire — someone who can dive deeply into the energy domain and build the analytics layer that’s crucial to our vision of cheap renewable energy on the grid. What you might work on • Mark-to-market and PnL calculations: we need to do real-time valuation of energy for every grid across thousands of locations, and turn that into a clear picture of profit and loss across the company. • Reconciliation and data quality: writing the tests that catch problems in our invoices before a trader or accountant does. • Data ingest and transformation: helping own the entire analytical data platform and building new ingest pipelines in python and flyte, or new models in DBT. You might be a good fit if you • Have modeled a complicated business domain into numbers people rely on, such as finance, billing, payments, settlements or revenue. • Write strong production SQL and are fluent in dbt: clean, well-designed models, tests, and documentation. • Are comfortable with python and can write data ingest and transforms. • Know how to store and query data efficiently in a warehouse: dealing with partitioning, incremental models, and managing cost. • Enjoy messy data and complex business logic, and is really good at finding discrepancies and tying out numbers. • Want to learn energy markets and trading. Prior experience isn't required. You might currently be a data engineer or analytics engineer. Nice-to-haves • Experience building trading, billing, accounting or other financial systems. • Orchestration tools like Flyte, Airflow, Dagster, or Prefect. • BigQuery, Postgres and dbt. Our stack: BigQuery, dbt Cloud, Python, Flyte and Grafana. Pay: $180–220k, plus competitive equity.

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