Work Experience
My professional journey and roles.
Senior Software Engineer
Led architectural migrations, backend API development, and team direction to ship modern, high-performance web applications.
Led the architectural migration of the core platform to a decoupled, TypeScript-based React SPA, replacing a server-driven UI to build more complex and maintainable features
Architected and delivered a new backend API using Python and FastAPI to support a new suite of on-demand machine learning tools and user management features
Recruited, onboarded, and directed a full-stack team of up to 4 engineers, owning feature development from conception to deployment
Established a new CI/CD pipeline with GitHub Actions to support the containerized Python and React services, automating all build, test, and deployment processes
Software Engineer
Developed and optimized full-stack applications and data pipelines for financial strategies, transforming complex quantitative models into user-friendly software.
Architected a full-stack options analytics platform on AWS for over 1,000 users, featuring a reactive WebSocket API and a server-driven SPA frontend that utilized React libraries for dynamic UI components
Engineered over 20 interactive financial charts with Highcharter to visualize complex options data, transforming raw data tables into actionable visual insights
Engineered a high-performance data scanner capable of rendering and filtering thousands of rows across 200+ columns in under one second, enhancing user data analysis capabilities
Analyzed user behavior with Heap analytics to identify and resolve friction points in key workflows, leading to a redesigned UI that increased feature adoption by 20%
Increased marketing leads by 5% and user engagement by 10% by developing an automated infographic generation and distribution service using React and AWS
Developed an end-to-end internal analytics dashboard, unifying data from disparate SaaS sources to establish a single source of truth for accurate business KPIs
Developed over 10 batch ETL data pipelines using AWS services to populate a MongoDB database, providing the core data for the options analytics platform
Engineered a specialized data pipeline with GCP BigQuery, writing complex SQL transformations to process over 500GB of historical financial data for algorithmic strategy backtesting
Centralized over 100,000 logs from 10+ AWS data pipelines into a Grafana and Loki stack, reducing daily monitoring time from over 30 minutes to minutes