Triet Pham

Intuit Expert Portal Insights team

Intuit Expert Portal's Insight team - Enhanced system reliability: Increased the availability of the Customer Serving Time system from 45% to 99.99%, reducing failed customer interactions by 90% by resolving an eight-month-long critical bug. - Optimized performance: Scaled the Contingency pipeline by 100x, increasing event-handling capacity from 50 to 5,000 events per minute. - High-impact contribution: Played a key role in enabling a new customer segment for Intuit Expert Portal, generating millions in revenue for the company. - Automation & efficiency: Developed an organization-wide tool to automate bot account logins, boosting engineer productivity by 5x. - User experience & performance optimization: Led the integration of a reusable UI widget flow that not only enhanced the experience for 15,000 customers but also enabled granular tracking of widget load times, helping identify and resolve performance bottlenecks efficiently - Technologies: React, Playwright, Spring Boot, Spark, Kafka, Stream Processing, Batch Processing, Postgres, Databrick, AWS DynamoDB, AWS Step Function, AWS Lambda, AWS ElastiCache, Redis, Cube, Docker, Kubernetes, Splunk, Wavefront, ArgoCD

QuickBooks Online Ecosystem Shell - UX Modernization team • Developed and managed the Health Plugin dashboard, enabling Intuit Quickbooks VPs, leaders, and managers to monitor and modernize their owned plugins by tracking outdated libraries and dependencies. • Implemented a comprehensive array of UI components, garnering recognition from 10 VPs and 17 leaders resulting in increased user adoption by 60% • Revamped the UI data flow through the implementation of Flux Pattern and Query caching, resulting in an impressive 80% enhancement in loading speed and overall performance. • Designed and deployed a high-performance key-value cache, optimizing data retrieval speed from 10-second-cost lengthy SQL queries to instant results • Employed distributed computing techniques to enable concurrent cache updates, significantly reducing the cache update time from 10 hours to 10 minutes. • Built an automatic tool to extract all CSS usages in all UI GitHub repositories, store in Data Lake and displays on the Dashboard • Technologies: React TypeScript, Java, Python, SpringBoot, AWS Lambda, AWS DynamoDB, AWS ElastiCache, Redis, Jenkins, GitHub, Splunk, GenAI

WhatsApp Business Integrity • Worked on Feature Limiting Framework - framework that manages all the limits of every WhatsApp User’s feature like sending messages, adding contacts, etc based on various signals • Developed a code generation tool utilized by 5 teams to automate onboarding for new WhatsApp features, reducing the onboarding time from 2 days to a mere 30 minutes • Optimized the Feature Limiting Framework by introducing cache layers, slashing the overall time required for querying feature limit data for 2 billion WhatsApp users by 80%. • Technologies: Hack, HackAST, PHP, React.js, GraphQL, Mercurial