Sigma Stream

I learned and applied Rust, Grafana, and Python to process high-frequency market data and capitalize on market inefficiencies.

Initially, our logic was implemented in Python, but we faced performance bottlenecks. We experimented with Go but ultimately chose Rust for its superior concurrency model and zero-cost abstractions, providing the performance and safety we needed. We also incorporated InfluxDB for time-series data storage and Redis for pub/sub message passing.

Working in a tight-knit team of five at a startup, we had a lot of ownership over our design decisions while maintaining frequent discussions to stay aligned. Concurrency and correctness were critical, so diving into Rust allowed us to develop a more efficient and reliable system. I was responsible for creating an order book synthesizer.