David Hsieh
Team Lead Integration Developer
Queensland, Australia
Summary
👤
Senior🎓
Top SchoolDavid Hsieh is a seasoned Team Lead and integration developer with 11+ years building scalable, maintainable .NET and Java enterprise systems across Australian government and private sectors. He specializes in cloud-native integrations and DevOps for Azure and Dynamics 365, shepherding legacy migrations and ARM-driven deployment standards while still coding APIs, serverless functions and front-end SPAs. David blends deep backend expertise (C#, .NET Core, SQL Server, PL/SQL) with modern front-end and DevOps toolchains (Angular, React, Azure DevOps, Docker), and has led small teams delivering production-critical citizen services. He contributes to open-source algorithmic trading tooling—adding and testing financial indicators to QuantConnect’s Lean engine—demonstrating a pragmatic testing-first approach. Comfortable translating complex business rules into auditable systems, he pairs a Master’s in Software Engineering with hands-on leadership and a knack for simplifying legacy complexity.
11 years of coding experience
13 years of employment as a software developer
Master of Engineering - MEng, Software Engineering, Master of Engineering - MEng, Software Engineering at The University of QueenslandBachelor of Information Technology, Software Engineering, Artificial Intelligence, Information Systems, Bachelor of Information Technology, Software Engineering, Artificial Intelligence, Information Systems at Griffith University
English, Chinese, German
Github Skills (9)
algorithm10
finance10
tradingview10
trading-algorithms10
csharp10
trading10
algorithmic-trading10
dotnet-core10
python4
Programming languages (4)
Github contributions (5)
QuantConnect/Lean
Apr 2015 - Apr 2016
Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:40 commits, 6 PRs, 39 comments in 11 months
Contributions summary:David's commits primarily focused on implementing and testing financial indicators within the Lean algorithmic trading engine. This included the development of new indicators such as the Stochastic, Average Directional Index, Donchian Channel, and On Balance Volume, along with related unit tests. The user also made adjustments and refactoring efforts on existing indicators.
algorithmic-trading-enginepythonpinescriptbacktesting-trading-strategiesc-sharp
kaffeebrauer/NinjaTraderIndicators
May 2015 - May 2015
Contributions:6 commits, 4 pushes, 1 branch in 1 day
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