• Contributed to a data migration script and it’s subsequent execution within an Azure Windows VM to transfer millions of dollars worth of transactional data from a separate ticketing system when onboarding six new West End theaters

• Improved the performance of the application’s financial reporting system by rewriting slow-running entity framework queries to T-SQL stored procedures as well as worked with U.K. clients to develop new reports tailored to their business practices

• Designed and successfully implemented season-ticket functionality by auditing all system design restrictions within the existing single-event purchasing process and discussing viable solutions with the director of systems development

• Monitored Azure’s app service and database metrics to gauge health of the overall system during periods of heavy traffic and queried Application Insights to help diagnose both production issues and performance bottlenecks in our checkout flow

• Replaced our legacy Windows Point Of Sale purchasing with a web based Stripe Terminal integration, communicated closely with client services to troubleshoot setup issues, and made simulator options configurable to allow other developers to easily test POS checkout without a physical card reader

• Co-led integration with the Telecharge ticketing system, expending months of planning, communication, and preliminary development to discover hidden impediments early on and avoid committing to potentially dangerous design decisions

• Implemented Apple Wallet integration, used XCode Simulator to troubleshoot ticket generation errors, and ensured our server was retrieving required images from our CDN instead of Azure Blob Storage

• Created support for multiple hostnames, giving our clients the flexibility to sell certain event series from any domain they choose

• Ported KissFFT algorithm from C to JavaScript by compiling the source code to WebAssembly bytecode and creating function wrappers/bindings to abstract away lower level memory allocation for the end user, providing an easy way for developers to access fast precompiled code for running CPU heavy signal processing on the web .

• Generated JavaScript performance benchmarks between the runtime speeds of .wasm, .asm, and .js implementations of the KissFFT algorithm by feeding a continuous stream of PCM data from the microphone to each algorithm, continually updating the average iterations per second for more accurate comparisons

• Displayed the high resolution frequency spectrum of live microphone stream by using D3 to continually re-render a graph of the newest frequency domain data generated from running the FFT on an incoming microphone signal