Summary
Zhuonan Song is a Staff Engineer based in Bellevue with 12 years of experience building large-scale data and ML platforms across Meta, Lyft, and Amazon. He specializes in interactive data platforms, data lake orchestration, and privacy-compliant data services, with multiple patents in indexing and scalability from his time at Amazon. At Lyft he helped position the company as a Trino community leader and accelerated business decisions through production ML/data infrastructure, and he now tackles ambiguity-driven problems in Global Integrity at Meta. Zhuonan blends deep distributed-systems engineering with a research mindset from Purdue, and consistently asks the next-level questions about cost/performance trade-offs, granular data inspection, and how to make data lakes and catalogs work for smaller organizations. He’s known for designing platforms that enable thousands of data scientists to collaborate efficiently while keeping privacy and compliance front and center.
12 years of coding experience
11 years of employment as a software developer
Bachelor of Science (BS) Computer Software Engineering, Bachelor of Science (BS) Computer Software Engineering at Fudan University
Master's degree Computer Engineering, Master's degree Computer Engineering at Purdue University
Bachelor's degree Computer Science, Bachelor's degree Computer Science at University College Dublin
Chinese, English