Carl Zhang

Designed and implemented Go-based streaming and workflow platforms with Kafka and Azure Functions, reducing API response times by 25% and improving throughput by 30%. Instrumented services with Prometheus/Grafana and automated tests to cut incident response times 45% and achieve >90% test coverage.

Built secure, high-throughput ML analytics data platforms with Go, Spark, and Airflow, achieving 99.99% uptime and processing over 5M daily events. Developed reactive ETL workflows and led accessibility improvements that increased usability by 20%.

Created low-latency account services with Go and .NET Core achieving 99.999% uptime for millions of users and architected distributed pipelines that increased throughput 35%. Enabled zero-downtime deployments and improved test automation to reduce regression cycles 40%.

Engineered scalable financial data services with Go and Java on Azure, authoring RESTful and gRPC APIs to accelerate partner integration. Integrated Prometheus/Grafana monitoring to reduce incident response times by 45%.

Developed interactive React/Redux applications with D3.js visualizations that increased user engagement 30% and optimized front-end performance. Containerized services with Docker and orchestrated deployments using Kubernetes to enable seamless scaling.

Completed a Bachelor of Applied Science in Computer Engineering at the University of Toronto from February 2014 to November 2019.