Owning Data Infrastructure That Scales to 200+ Production Merchants.
I own backend and data platforms from system design through migration, production operation, and recovery. Rearchitected data ingestion from legacy cron-based batch (days-late) to real-time CDC with sub-5-minute freshness for webhook-capable platforms, up to 6 hours for others.
Mission-Critical Production Engineering
Start with the data platform, then the production incident it survived — these show architecture ownership and operational judgment fastest.
The Data Platform
Owned the rebuild of customer and order data infrastructure across 200+ merchants on five commerce platforms; freshness ranges from sub-5-minute (webhooks) to ~6 hours (legacy) vs. days-late baseline.
Identity Resolution
Architected deterministic identity resolution across email, device, cookie, phone, and platform IDs on a legacy, highly-distributed profile system — merging ~15%+ of contacts into an existing identity across ~200-300 merchants.
Customer Segmentation
Owned the query model and builder that let Customer Success create audiences from four source systems without routine engineering tickets.
Recommendation Blocks
Owned the trust ladder, serving system, and adoption measurement for a recommendation product built from zero.
Hard Problems & Learnings
Ten production incidents that shaped engineering judgment. Lock contention at scale, silent failures, architectural incompatibility, database constraints, resilience patterns, leadership under crisis.
Hiring Thesis
I work best owning backend and data infrastructure systems end-to-end. I'm drawn to roles where I can influence architecture across multiple teams, lead small teams through scaling, and own both technical direction and operational reliability.
Real Failures, Honest Root Causes, Measurable Mitigations.
A decade of production lessons: query shape, lock contention, silent data failure, memory pressure, and the judgment to trade freshness for stability when the system needs it.