Project SOW

Validation Pipeline Build

Data quality engineering · automated validation · GS1/GTIN compliance checks

The audit found $458,000 a year in chargebacks and traced every one to the field that caused it. Twelve months later, the same defects are back — because the audit fixed the data, and nothing fixed the flow.


An audit is a snapshot; data defects are a flow. They enter through manual entry, partner files, broker submissions, and system handoffs — and unless something checks the data beforeit lands, this year’s findings become next year’s findings with new dates. The fix is a validation layer: automated checks that run where the defects enter, with a defined path from every flag to its resolution.

This engagement is the natural second purchase. The audit tells you what’s broken and what it costs; the pipeline is what keeps it fixed.

The standards the pipeline enforces — GS1/GTIN anatomy, GDSN attribute requirements, retailer item-setup rules, and logistics dimensions — are covered in the Data Standards Cheat Sheet.


What gets built

Inbound validation that runs before data enters your systems: format and type checks, phantom-duplicate detection, GS1/GTIN validation, dimension-and-weight integrity, and retailer-specific rules for the partners you ship to. Item-setup preflight — new-item forms checked against the retailer’s schema before submission, not after rejection. And an exception-handling protocol: every caught defect gets an owner, a path, and a resolution state, so quality stops depending on who happens to notice.

The pipeline is documented and handed off. It runs without me — that’s the point.


See it worked through

The architecture is public, end to end:

Cinderhaven data platform

A modern source-to-mart data platform for CPG data shapes: pipelines, data quality testing, orchestration, and lineage. Python, Postgres, dbt, Dagster.

github.com/MsShawnP/cinderhaven-data-platform →

Item-setup preflight

Codified partner schemas and a typed validation engine that flags new-item form rejection risk before submission.

github.com/MsShawnP/item-setup-form-preflight →

Dimension & weight integrity

Validation for the dim-weight defects behind freight chargebacks and compliance fines.

github.com/MsShawnP/dimension-weight-integrity →

What you get

A defined SOW: scope, timeline, fixed deliverables, clear finish line. Typically 4–8 weeks depending on system count. The deliverable is a running pipeline, its documentation, and a team that knows how to operate it.

Start with a conversation.

Bring your audit findings — mine or anyone’s  — to a thirty-minute call. The pipeline scope falls out of the findings list. No deck, no obligation.