Kexiang Wang is a software engineer with seven years of experience building high-performance back-end systems, currently based in Old Toronto and working at Fireworks AI. He spent three years at RisingWave contributing core SQL functions, CDC improvements, and performance optimizations to a prominent open-source stream processing platform, demonstrating deep familiarity with databases and real-time data pipelines. Prior roles at ByteDance and MEGVII sharpened his production engineering skills in large-scale, latency-sensitive environments. He holds a MASc in Electrical & Computer Engineering from the University of Toronto and a BE in Computer Science from Beihang University, combining academic rigor with practical system design. Colleagues describe him as someone who balances careful refactoring with targeted feature work, quietly improving internals that yield measurable performance gains. He often gravitates toward database-facing problems and stream processing challenges that benefit from both algorithmic thinking and pragmatic engineering.
7 years of coding experience
5 years of employment as a software developer
Bachelor of Engineering - BE, Computer Science and Technology, Bachelor of Engineering - BE, Computer Science and Technology at Beihang University
Master of Applied Science (MASc), Electrical & Computer Engineering, Master of Applied Science (MASc), Electrical & Computer Engineering at University of Toronto
High School, High School at The affiliated High School of Shanxi University
The event stream processing platform for developers. Unified experience for real-time data ingestion, stream processing, and low-latency serving. Best-in-class performance and cost-efficiency. Supports SQL and Python.
Role in this project:
Back-end Developer
Contributions:358 reviews, 51 commits, 207 PRs in 1 year
Contributions summary:Kexiang primarily contributed to the back-end functionality and database management of the stream processing and management platform. Their work involved adding and modifying features related to the SQL functions, especially the `to_jsonb`, `make_time`, and `has_privilege` functions. Further commits reflect changes to the CDC component and optimization in the codebase, indicating a focus on improving the core performance of RisingWave. The user also touched on the internal structure with some refactors.
The flexibility of Python with the scale and performance of modern SQL.
Contributions:55 pushes, 4 branches in 3 months
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