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Every case study here answers one question: measurable outcome.
data-pipeline-validation-gateway.mdZapier
Data Pipeline Validation Gateway
ShippedTeam: Data + Eng
TL;DR
Partnered on validation gateway logic that cut customer-reported data errors by 40%.
Outcome
- ↓40%customer-reported data errors, post-launch
Saw It
- Partnered with engineering on validation gateway logic to catch bad data before it reached customers.
↓→
Figured It Out
- Partnered with engineering on validation gateway logic, pipeline rules, and customer-facing data quality workflows.
↓→
Did It
- Shipped the validation gateway.
- Result: a 40% reduction in customer-reported data errors.
My Role
Partnered with engineering on the logic and rules.
Full breakdown
Problem & Risk
Bad data was reaching customers before this gateway existed, generating reported errors.
Timeline
git log --oneline⏱ -40% errors
kickoff: validation gaps generating customer-reported errorsPhase 0
discovery: partnered with engineering on validation gateway logicPhase 1
ship v1: pipeline rules and quality workflows livePhase 2
next: customer-reported errors reduced 40% post-launchNext
What We Did
Partnered with engineering on validation gateway logic, pipeline rules, and customer-facing data quality workflows.
~ rough sketch, not an actual screenshot ~
bad data reaching customers
validation gateway logic + pipeline rules
-40% customer-reported errors
Who Benefits
Customers see fewer data errors reaching them.