Description
We’re looking for someone passionate about energy & electricity markets with deep expertise in analytics reporting & SQL frameworks who can help develop our analytics platform.
As a power company driven by ML and data, your scope would include automating gross margin, domain modeling, and revenue reporting, which help us measure real-time financial health and risk across all lines of our business. You would also deeply embed with Gridmatic teams to build fundamental data products that help model Gridmatic’s business domains for real-time analytics.
What you might do:
- Build an end of month accounting pipeline in dbt for our retail electricity business
- Translate raw, complex external data (e.g. billing and settlement reports) into clear and cohesive internal data products
- Create a dashboard to track financial exposure across asset lines (e.g. commodity trading, retail electricity contracts, energy storage assets)
- Convert existing python notebooks and excel workbooks into dbt pipelines
You might be a good fit if you:
- Have had 3+ years of experience in analytics engineering or similar roles.
- Have strong technical skills in SQL, dbt, and data warehouses (e.g. BigQuery, Snowflake).
- Are highly effective at talking to stakeholders to solve complex business problems and to understand messy domain-specific data sources.
- Have enough software engineering skills to be dangerous. Python experience isn’t strictly necessary but is a big plus.
- Have worked on financial analytics or PnL data. Not a requirement, but would be a big plus.
- Energy experience is not strictly required, but a successful engineer in this role will be proactive in learning and understanding the specifics of energy domain data and financial concepts, with minimal hand-holding from business domain experts.
This role requires candidates to adhere to our hybrid policy, 3 days a week in office with at least 1 day in our Cupertino office.
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