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

In a solar companies business, the reporting problem is rarely a missing chart. It is that monitoring-platform output data and supplier delivery records arrive in different formats, on different schedules, with different definitions, so every report starts with reconciliation and ends with doubt. Pipelines remove that reconciliation step by standardising data before anyone reports on it.

The build follows the decisions, not the data. The company runs on surveys and installs: roofs surveyed, systems designed, approvals secured, crews scheduled, and customers who judge everything on the first bill after install. The metrics that matter are the ones managers ask for in meetings, and the warehouse is organised around answering those questions consistently.

The warehouse is built to be run by the business, not by its builder. Scheduled pipelines, visible failure alerts, and a runbook mean the team can keep the numbers flowing and add sources without specialist help.

The reports that matter are the ones the team already rebuilds by hand: lead-to-install conversion, install lead times against approval stages, system output against design estimates, crew utilisation, and referral rates by install. 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.

Most solar companies businesses already run on CRM (leads and customers), design software (system designs), scheduling software (surveys and installs), supplier catalogues (panels and inverters), and monitoring platforms (system output). The pipeline work starts from those systems as sources, not by replacing them, and lands the cleaned data in a warehouse the business owns, with dashboards on top for the team.

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

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

CRM handles leads and customers. design software handles system designs. scheduling software handles surveys and installs. supplier catalogues handles panels and inverters. monitoring platforms handles system output.

The realistic outcome is a weekly meeting run on trusted numbers: lead-to-install conversion and install lead times against approval stages arrive on schedule, definitions are no longer debated, and surveys booked without roof details becomes visible early enough to act on. That is the standard this engagement is measured against, not a dashboard launch.

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.