About us

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.

Why Now?

The energy market is going through its biggest shift in 50 years. We no longer just supply electricity, we make it intelligent. RABOT is growing at triple-digit rates — and with every new customer, every new product and every new partnership, the volume of data we need to make sense of grows too.

Our stack is in place: BigQuery, dbt, Metabase. What matters now is the layer in between — clean models, tested logic, unambiguous definitions. A number is only as reliable as the model it comes from. That is where you come in: an experienced person who turns business logic into versioned code instead of into the 200th Metabase question.

Your Mission

You own the layer between raw data and decisions. You model our data in dbt on BigQuery — from staging through core to the marts — keep the models reliable through tests, reviews and documentation, and keep an eye on run times and cost.

Upstream you work with Data Engineering on ingestion, data quality and clear interfaces. Downstream you work with BI and the business functions: you turn business logic into certified, documented models with unambiguous definitions. The point is not that you build every request yourself, it is that analysts and business teams can answer their own questions on your models instead of queuing for analytics capacity.