Renewable energy jobs · Data Engineering

Data Engineering Jobs in Renewable Energy

Data engineers build and maintain the pipelines that move meter readings, turbine telemetry, and market prices from raw sources into the databases and models that run a modern energy company. In renewables the volume is the point: Europe had roughly 225 million smart electricity meters installed by 2024, each producing a stream of time-series data that has to be ingested, cleaned, and stored before anyone can forecast demand or settle a bill.

That scale is what separates energy data engineering from the generic version of the role. A retailer's checkout events arrive in predictable bursts; a grid's data never stops. Octopus Energy's Kraken platform processes over 300 million meter readings a day across 17 countries, and its data team grew from 15 people in 2021 to more than 700 staff working with data by 2025, according to Databricks. Pipelines built on dbt, Spark, and cloud lakehouses are what let flexibility platforms dispatch home batteries and EV chargers in near real time.

What the work actually involves

The core job is unglamorous and essential: ingest SCADA feeds, weather forecasts, and metering data; reconcile them against messy reference tables; and expose clean, versioned datasets to analysts and data science teams. In wind and solar operations that means handling sensor drift, gaps, and duplicate timestamps from thousands of assets. On the trading side it means sub-second latency, so that virtual power plant and balancing systems act on current prices rather than stale ones. Most postings ask for SQL, Python, one distributed-processing framework such as Spark or Flink, and orchestration with Airflow or Dagster.

Who is hiring

Demand splits across three employer types. Grid operators and large utilities - Enexis in the Netherlands, Vattenfall, Southern California Edison - hire data engineers to modernise decades-old metering and asset systems. Energy-software firms such as Octopus and Gridmatic treat the data platform as the product itself. And a growing tier of climate-tech startups builds forecasting and optimisation tools where a three-person data team carries the whole business. Listings cluster in London, Hamburg, Berlin, Amsterdam, Melbourne, and Toronto, tracking where both grid-modernisation budgets and software talent sit.

Titles, pay, and where the field is heading

Most roles are advertised plainly as Data Engineer or Senior Data Engineer, with Staff and Platform Engineer titles at the top of the ladder. In the UK a data engineer averaged around £52,600 in 2025, well above field metering roles, and grid-optimisation and forecasting positions in the US, Germany, and Australia can reach six figures. The premium goes to engineers who pair the standard stack with domain knowledge: knowing what a half-hourly settlement period is, why curtailment (deliberately switching off generation the grid cannot absorb) shows up as missing data, or how balancing markets clear.

The direction of travel is toward real-time processing and toward AI. As AI for energy and machine learning move from pilots into demand forecasting and predictive maintenance, the constraint is rarely the model itself; it is whether the data feeding it is reliable. That is what makes the engineers who build those foundations, alongside the energy analytics specialists who consume them, among the harder hires in the sector to fill.