Gridmatic

AI-driven optimization of renewable assets

Software Engineer - Analytics Platform

Data EngineeringConfirmed live in the last 24 hours

Full-timeCupertino, CA, USAIn-person

About the Job

Requirements

Have strong production Python and SQL skills and have built backend services and APIs.
Be highly capable in data modeling with relational databases and data warehouses.
Have built systems that handle messy real-world data, including late arrivals, corrections, and backfills.
Understand how to scale datasets across long time horizons and many customers.
Be able to work in an ambiguous startup environment with people across teams.
Be willing to learn the energy markets and trading domain; prior experience is not required.
Have worked extensively with data systems as a software engineer, or have strong software skills as a data engineer.

Responsibilities

Design and build core data models and entities for trades, assets, renewable supply, and energy contracts.
Build pipelines to ingest data from financial exchanges and grid operators.
Improve the data platform, based on BigQuery, dbt, Flyte, and Kubernetes, so engineers and analysts can ship changes quickly.
Improve AI’s understanding of company data so people across the company can get accurate answers to business questions.

Desired Qualifications

Have experience building trading, billing, accounting, or other financial systems.
Have experience with orchestration tools such as Flyte, Airflow, Dagster, or Prefect.
Have experience with BigQuery, Postgres, and dbt.
Have experience with React for internal tools.

The role

Gridmatic trades power, runs battery storage, buys renewable supply and sells electricity to retail customers. We’re looking for a startup-minded software engineer who’s great with data: you'll build the data systems our business runs on, designing core data models for trades and assets, building the pipelines that bring in outside market and settlement data, and automating the steps in between.

What you might work on

Core data models: we design and build the core entities that the company relies on: trades, assets, renewable supply, and energy contracts, which power our financial understanding of all aspects of the business.
Data ingestion: we build pipelines to ingest financial exchanges and grid operators.
Data platform: we’re continually improving our platform (based on BigQuery, DBT, Flyte, and Kubernetes) so engineers and analysts can ship changes quickly.
Self-serve analytics: improving AI’s understanding of our data so that people across the company can get accurate answers to important business questions.

You might be a good fit if you

Have strong production Python and SQL skills, and have built backend services and APIs.
Are really good at data modeling, both with relational DBs and data warehouses.
Have built systems that deal with messy real-world data: late arrivals, corrections, and backfills.
Understand how to scale datasets across long time horizons and lots of customers.
Can thrive in an ambiguous startup environment, working with people across many teams to solve important problems.
Want to learn the domain of energy markets and trading. Prior experience isn’t required.

We’re looking for a software engineer that has worked extensively with data systems, or a data engineer with strong software skills.

Nice-to-haves

Experience building trading, billing, accounting or other financial systems.
Orchestration tools like Flyte, Airflow, Dagster or Prefect.
BigQuery, Postgres and dbt.
React, for internal tools.

Pay range: $175-270k, plus competitive equity

Taking care of you today:

- Continuing Education Opportunities

- Flexible PTO

- Medical, Dental and Vision plans with competitive employer contributions

- Pre-Tax commuter benefits

- $1500/year non profit donation matching program through Millie

- Home Office Stipend

Protecting your future for you and your family:

- 401K contribution match up to 4%

- Company-paid parental leave

- Company Paid Life Insurance

- Stock Option Loan Program

About the Company

Gridmatic

AI-driven optimization of renewable assets

Gridmatic uses artificial intelligence to improve the profitability and reliability of renewable energy assets. It serves three client groups: generators of renewables, operators of energy storage, and consumers of renewable energy. The product suite analyzes market data with machine learning to forecast energy prices, manage price and performance risk, and optimize revenue from energy transactions—especially for storage assets that must balance risk and availability. Unlike others that focus on a single segment, Gridmatic combines AI analytics with energy market expertise to optimize both generation and procurement across markets. Its goal is to accelerate clean energy adoption by making renewable energy cheaper, more predictable, and easier to deploy at scale, supporting decarbonization and a more reliable grid.

Company size: 51-200
Company stage: Early VC
Total funding: $6M
Headquarters: Cupertino, CA
Founded: 2020

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