Yaohua Zhao is a Senior Software Engineer based in Shanghai with five years of experience building large-scale data and privacy-preserving ML systems, currently working on AIML privacy initiatives at Apple. He has deep backend expertise from roles at Databricks and Oracle, contributing to ingestion, streaming, Delta Lake, and Databricks SQL features such as Auto Loader and streaming tables. An active open-source contributor, Yaohua helped land Spark 3.3.0 improvements exposing hidden file metadata and enhanced Delta Lake table/vacuum behaviors, demonstrating a knack for pragmatic performance and usability gains in widely used projects. His background in systems and parallel computing (MS, UT Austin) complements hands-on work with transactional and streaming data platforms. Colleagues would describe him as someone who balances careful refactoring and error-handling with measurable performance wins. He brings a subtle but valuable focus on making metadata first-class in data systems—improving queryability and stream integration in production workloads.
5 years of coding experience
7 years of employment as a software developer
High School Diploma General Studies, High School Diploma General Studies at Xinjiang Bazhou Petroleum No. 1 High School
Master of Science - MS Software Engineering and Systems, Master of Science - MS Software Engineering and Systems at The University of Texas at Austin
Bachelor of Engineering Electrical and Electronic Engineering, Bachelor of Engineering Electrical and Electronic Engineering at The University of Manchester
Bachelor of Engineering Electrical and Electronic Engineering, Bachelor of Engineering Electrical and Electronic Engineering at North China Electric Power University
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
Role in this project:
Backend Developer
Contributions:4 reviews, 10 commits, 6 PRs in 1 year 10 months
Contributions summary:Yaohua contributed to the Apache Spark Delta project by refactoring and improving the codebase. Their work involved modifying commands related to table creation and vacuuming, enhancing error messages, and reorganizing code. They also made minor updates to the sbt install script and corrected tests, showing a focus on code quality, maintenance, and error handling within the Delta Lake framework.
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer
Contributions:90 reviews, 4 commits, 21 PRs in 2 months
Contributions summary:Yaohua primarily contributed to improving Apache Spark SQL's handling of hidden file metadata. Their work involved implementing new interfaces and features to expose file metadata as built-in hidden columns, allowing users to query file-related information. The user also focused on schema pruning and filtering files based on metadata, leading to performance improvements. Furthermore, they enhanced the system by supporting the integration of metadata within streaming operations, improving the platform's ability to handle file metadata in various use cases.
analyticspythondata-processingsqlapache
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