Hire Data Engineer for Manufacturing
Senior, direct, no layers

As a manufacturing business grows, manual reporting scales badly: more sources, more spreadsheets, more versions of the truth, and material shortages stopping a line discovered weeks after it started. The pipeline approach scales differently, because each new source is modelled once and then serves every report.

What the business already records is the raw material. production scheduling data and machine and sensor data may be messy, but they are real, and modelled carefully they answer on-time delivery by product line and machine downtime causes without new data collection.

Rollout is deliberately narrow: one pipeline, one report, one decision at a time. Each piece must prove the number is trusted before the next source is added, which is why supplier delivery data feeding on-time delivery by product line usually comes first.

The reports that matter are the ones the team already rebuilds by hand: on-time delivery by product line, defect rates by stage and shift, machine downtime causes, material lead-time reliability, and margin per order. 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 manufacturing businesses already run on ERP (orders, inventory, and production), production scheduling (shop-floor plans), quality systems (inspections and defects), supplier portals (materials and lead times), and accounting software (job costs). 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 defect rates by stage and shift. When that report arrives on schedule, correct, and without manual work, the case for pipelining the remaining sources makes itself.

Take ERP order and inventory records. It is the kind of source every manufacturing business has and nobody quite trusts. Once it flows through a tested pipeline with error logging, defect rates by stage and shift stops depending on whoever happened to build last month's spreadsheet.

ERP handles orders, inventory, and production. production scheduling handles shop-floor plans. quality systems handles inspections and defects. supplier portals handles materials and lead times. accounting software handles job costs.

The realistic outcome is a weekly meeting run on trusted numbers: on-time delivery by product line and defect rates by stage and shift arrive on schedule, definitions are no longer debated, and production scheduled by gut feel 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.