I'm a Strategy R&D engineer focused on fintech, trading-data platforms and quant-product backends, with hands-on experience across high-throughput backend systems, event-driven architecture, real-time data processing and financial-product development.
I currently own the real-time market-data, historical-data and backtesting infrastructure for TW and US equities: using Python, FastAPI, Redis Streams, PostgreSQL / TimescaleDB and Docker to build a Market Data Platform supporting high-frequency streams, live snapshots, historical export and hot/cold data tiering.
My career began in backend systems and bespoke project delivery — third-party payment integration, government tenders, blockchain arbitrage trading systems — building end-to-end capability from requirements to system design, data modeling, backend development and deployment/ops, with an engineering mindset centered on data consistency, maintainability, performance and long-term extensibility. I've led a 5–8 person backend team building a group ERP microservice suite, integrating a RabbitMQ cluster, planning database architecture and training interns.
In 2025 my ML + generative-AI financial anti-fraud solution won the Taishin Financial Holdings group Merit Award at the “Cloud Surge: Taiwan Generative-AI Application Hackathon.” I keep investing in financial data engineering, quant-research infrastructure and AI applications in finance.