Hire Data Engineer for Retail Shops
Senior, direct, no layers

In a retail shops business, the reporting problem is rarely a missing chart. It is that supplier delivery data and footfall and promotion 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 shop runs on stock and footfall: deliveries unpacked, shelves faced, seasons changed, and regulars who come back because someone remembered their size. 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 warehouse draws on supplier delivery data, footfall and promotion records, point-of-sale transactions, inventory and reorder records, and e-commerce orders. Each source is pulled on a schedule, checked for duplicates and missing records, and modelled into tables the business can query, so sell-through by product and season, stockout rates on bestsellers, and online versus in-store sales mix all read from the same definitions instead of separate extracts.

Day to day, the business already runs on point of sale (sales and stock), inventory software (levels and reorders), e-commerce platform (online sales), supplier ordering (replenishment), and review platforms (local reputation). Pipelines pull from those sources on a schedule, models define the metrics once, and the reporting layer serves every team from the same definitions.

A sensible first project is one pipeline done properly, often supplier delivery data feeding sell-through by product and season, with the team using the resulting report for real decisions before anything else is added. A pipeline that proves itself on one decision earns the trust to carry the rest.

Take supplier delivery data. Today it probably arrives as an export someone cleans by hand. In the pipeline it is pulled on a schedule, checked for missing or duplicate records, and modelled into the same definitions every report uses, so sell-through by product and season is a number the team trusts instead of a spreadsheet they debate.

point of sale handles sales and stock. inventory software handles levels and reorders. e-commerce platform handles online sales. supplier ordering handles replenishment. review platforms handles local reputation.

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.

That also changes how the business argues: disagreements move from whose spreadsheet is right to what the number means and what to do about it, which is where a retail shops team's judgement actually adds value. Browse all hire engagements or discuss your data setup directly.