Zane T. Email & Phone Number

- Revamped Ramp’s financial dashboard using React.js, TypeScript, and Next.js, improving load times by 40% and boosting NPS by 30%.- Built reusable frontend components with React Hooks, Redux Toolkit, and GraphQL, increasing user retention by 20% and earning 4.8-star post-release ratings.- Optimized UI styling using Tailwind CSS, improving code maintainability, reducing the CSS payload by 50%, and enhancing responsive performance on mobile devices.- Architected a micro-frontend system using Single SPA, React.js, and Docker, facilitating independent development and deployment across multiple teams.- Implemented real-time user tracking using Kibana and Elasticsearch, reducing troubleshooting time by 25% and improving system reliability by 20%.- Automated testing with Jest, Cypress, and Enzyme, achieving 90% code coverage and reducing bugs in production by 40%.- Enhanced CI/CD pipelines with GitHub Actions, Docker, Kubernetes, and Terraform, cutting deployment times by 35% and reducing deployment failures by 20%.- Mentored junior engineers, conducting code reviews and providing guidance on best practices, fostering a culture of continuous improvement.

New York, New York, United States

- Engineered the frontend of Amazon’s e-commerce shopping cart and checkout system using React.js and Next.js, significantly improving load times and enhancing the shopping experience for millions of users globally.- Designed and built scalable APIs using Node.js, Express.js, and GraphQL, optimizing data flow and reducing latency for real-time recommendations.- Architected serverless microservices on AWS with Lambda, API Gateway, and DynamoDB, ensuring seamless scaling during peak events like Prime Day.- Enhanced backend performance by refactoring APIs, optimizing Amazon Aurora (PostgreSQL) queries, and integrating Redis caching, improving data retrieval speeds platform-wide.- Developed high-performance microservices in Node.js, Java, C#, and Python, emphasizing scalability.- Implemented CI/CD pipelines with AWS CodePipeline, Jenkins, and Terraform, automating deployments and reducing errors by 25%.- Integrated machine learning models with SageMaker, enabling personalized recommendations and boosting conversion rates through data-driven insights.- Collaborated with cross-functional teams (product, data science, ops) to deliver large- scale features, ensuring alignment with business priorities and user needs.- Ensured security and compliance by implementing OAuth 2.0 and AWS IAM policies, safeguarding sensitive user data and meeting industry standards.