Hire Data Engineer for Energy Companies
Senior, direct, no layers

Most energy companies businesses do not need more dashboards. They need the unglamorous work underneath: data pulled from each source on a schedule, checked for errors, modelled into consistent definitions, and delivered to one reporting layer the team can trust.

The shape of the data decides the shape of the build. The business runs on meters and margins: tariffs priced against wholesale, installs scheduled around weather and grid approvals, and customers who switch the moment a bill surprises them. Sources, models, and dashboards follow from that, not from a standard template, which is why two businesses in the same industry still end up with different pipelines.

Handover is part of the deliverable: documented models, scheduled pipelines the team can monitor, and dashboards the team can extend. The business should not need the person who built it to keep the numbers flowing.

The reports that matter are the ones the team already rebuilds by hand: churn by tariff and tenure, install lead time against approval stages, margin per customer after wholesale costs, engineer utilisation, and quote-to-install conversion. Each is rebuilt once from modelled data and then refreshed on a schedule, so the weekly meeting starts from numbers everyone trusts instead of a debate about whose spreadsheet is current.

Day to day, the business already runs on CRM (customers and tariffs), metering platforms (usage data), scheduling software (installs and engineers), billing systems (invoices and payments), and quote tools (tariff and install quotes). Pipelines pull from those sources on a schedule, models define the metrics once, and the reporting layer serves every team from the same definitions.

The first build is usually the report the team rebuilds by hand most often, often install lead time against approval stages. When that report arrives on schedule, correct, and without manual work, the case for pipelining the remaining sources makes itself.

Take billing and payment records. It is the kind of source every energy companies business has and nobody quite trusts. Once it flows through a tested pipeline with error logging, install lead time against approval stages stops depending on whoever happened to build last month's spreadsheet.

CRM handles customers and tariffs. metering platforms handles usage data. scheduling software handles installs and engineers. billing systems handles invoices and payments. quote tools handles tariff and install quotes.

The measure that matters is use months later. Pipelines still running on schedule, reports still opened weekly, and new sources added without rebuilding the warehouse is the deliverable. Anything that needs its builder to survive was not finished.

Over time the warehouse becomes an asset of its own: every new question starts from modelled data instead of a fresh export, so analysis gets faster the longer the system runs. Browse all hire engagements or discuss your data setup directly.