Data engineer building the pipelines behind AI products — turning raw, inconsistent client data into clean, model-ready datasets that ship. Grounded in information architecture, headed toward cloud architecture for AI/ML workloads.
Designed and built end-to-end data pipelines for small-business client engagements — ingesting raw spreadsheets, exports, and operational databases and transforming them into clean, structured datasets that powered shipped AI products. Partnered with AI engineers on schemas and data requirements across multiple concurrent client projects, applying production-grade practices in Python and SQL.
Directed a cross-functional team of 3 to deliver a client-approved mobile app prototype on schedule. Designed user flows and information architecture for booking, pest identification, accounts, and scheduling — and served as the main client liaison, cutting revision cycles through weekly check-ins and formal presentations.
Architected the system structure for ASCA's Administrator Development Program — data structures and user flows scaling to 400+ mentors and mentees, fully replacing spreadsheet-based program management. Delivered a developer-handoff-ready prototype, presented to the CSU Fresno Department Chair and Dean.
Led shift teams in a high-volume café — owning end-of-day reconciliation and POS inventory tracking, keeping inventory variance below 2% with accurate daily financial closes.
Building data infrastructure for AI — and looking for the next hard problem. Let's talk.
pcnguyen129@gmail.com