Software Engineer @ Big Data Federation, Inc. | Backend Development | Auto Trading System | Machine Learning | Cloud Services |
Software Engineer with 5+ years of experience in backend engineering and building automated trading systems. Proven ability to design, develop, and deploy high-performance, scalable, and reliable systems. Proficient in Python, Flask, Database, R Language, as well as financial markets and trading algorithms.
Developed a fully automatic trading system to manage a private fund, covering US and international markets and executing sophisticated trading strategies based on real-time market signals.
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Developed 10+ trading modules for equities, options, foreign exchange and futures markets, enabling the system to execute 20+ types of orders including algo trading orders.
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Created 20+ market data endpoints and deployed on AWS, providing high-quality real-time market data.
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Improved system stability, resulting in 99% uptime hence significantly reduced the workload of maintenance. Also transition away from having a 24/7 on-call support team, resulting in substantial cost savings.
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Integrated third-party APIs, brokerage gateways and financial data sources to expand platform functionality.
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Implemented backtesting and optimization frameworks for recurring evaluation and refining trading
strategies, resulting in consistently outperforming the market baseline by an impressive 2-3%.
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Managed over 50 million trade records daily with a dedicated database and built high-performance RESTful APIs to facilitate swift data storage and retrieval.
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Created cloud-based database server on AWS EC2 from scratch, using Clickhouse database — a
renowned open-source solution well-suited for handling substantial volumes of time series data with
SQL-like queries. Crafted dedicated scripts for data cleaning and seamless ingestion processes.
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Built robust APIs using Flask to exploit both raw and aggregated data for making trading decisions and training prediction models.
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Optimized database queries and API logic, reducing API response time by 50% and ensuring the
performance when users requesting multi-million rows of data.
Leveraged Python Flask and a JavaScript charting library Highcharts to build data visualization pipeline, translating market data into trading insight. Integrated data delivery to Slack chatbot and Twillio SMS service
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Deployed and maintained web backend APIs on AWS, accomplished with a robust CI/CD tool Jenkins
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Collaborated with data scientists and trading strategists, delivering profitable strategies with high-quality code