David Bui

Led the migration of a monolithic application to microservices architecture using Kafka, RabbitMQ, and Azure Functions, reducing infrastructure costs by 25% and increasing business savings by $250,000 per month. Migrated legacy on-premises infrastructure to Azure focused on SaaS integration, reducing maintenance costs by 50% and significantly improving scalability. Improved application performance by optimizing SQL Server queries, leading to a 30% reduction in query execution time. Resolved a critical bug affecting 5000+ users, boosting customer confidence by 95%. Conducted load testing with JMeter for peak periods supporting 5000 concurrent users. Enhanced code quality and team productivity by conducting code reviews and mentoring junior engineers.

Upgraded legacy web applications using ASP.NET Core, Node.js, Angular, and React, improving performance by 20% and user satisfaction by 25%. Introduced GraphQL and Next.js to implement SEO-friendly features, reducing development time by 15%. Led adoption of cloud microservices with AWS Lambda, reducing infrastructure costs by 20% and enhancing performance by 30%. Integrated RESTful APIs including payment gateways and social platforms, boosting user engagement by 40%. Implemented CI/CD pipelines with AWS Code Pipeline and Kubernetes, cutting deployment cycle time by 70% while ensuring scalability. Achieved a 98% bug-free release rate through extensive testing. Collaborated cross-functionally to deliver projects with 95% accuracy on deadlines and requirements.

Developed 10 web applications supporting payroll, HR, talent, and performance management with Laravel, MySQL, and Angular. Created a real-time chat application using Node.js, Express.js, MySQL, and React, reducing churn rate by 60%. Built three scalable microservices for healthcare clients using .NET Core, Docker, and Kubernetes, cutting infrastructure costs by 75% and improving performance by 50%. Optimized a large-scale legacy app's performance by 95% with ASP.NET, C#, and MySQL. Coordinated Azure migration for legacy applications, minimizing downtime by 20%. Fine-tuned SQL queries resulting in a 25% reduction in response times and enhanced database performance.