
Rabot Energy is an independent provider of dynamic electricity tariffs with 100% green energy. Through our innovative procurement strategies, we ensure both ecological sustainability and cost optimization in home energy management. By passing on wholesale electricity market prices directly to our customers, we are able to reduce their electricity bills by an average of 35%.
Owners of electric vehicles and smart meters benefit particularly from our dynamic electricity tariff, as they can automatically charge their vehicles at home when electricity prices on the exchange are especially low. In the Rabot Energy app, charging preferences can be easily set and current market electricity prices can be tracked in real time.
With our intelligent charging solutions, we actively contribute to increasing the share of renewable energy in Germany’s overall electricity consumption.
Our vision is to give every customer the opportunity to manage their energy consumption in a smart way while conserving the environment and natural resources. By offering smart charging and energy management solutions, Rabot Energy actively helps drive the energy transition forward. With this idea, we have already won the trust of over 100,000 customers.
The energy market is going through its biggest shift in 50 years. We no longer just manage electricity, we make it intelligent. RABOT is growing triple digits — and with every new customer, every new product and every new partnership, the amount of data we need to make sense of grows too.
Now we're taking our reporting and analytics to the next level: reliable, data-driven and built for the whole company. That's where you come in — someone who turns raw data into decisions.
You're the person who turns data into clarity at RABOT. You collect and model data from different sources, build dashboards and reports, and turn them into insights that teams from Commercial to Operations to Pricing can rely on.
You work closely with the departments: you understand their questions, define the right KPIs together, and translate "could we get a look at…" into solid analysis. You make sure our numbers are consistent and reliable — one shared data foundation instead of five different truths. And you think beyond the next report: you spot patterns, deliver "so what" insights and help us make decisions based on data rather than gut feeling.
We think in outcomes, not task lists. If you're successful, here's what that looks like:
Month 3 (Ramp-up)
Month 6 (Performance)
Month 12 (Scale)
Bonus: Knowledge of Python or R, experience with ETL/data pipelines and cloud data warehouses (e.g. BigQuery or Snowflake), a basic understanding of statistics and forecasting, and experience in the energy sector or another data-heavy, regulated industry.
IR, Legal & Finance
Berlin, Germany
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