Xinyi Yu
Software Engineer at Databricks
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolXinyi Yu is a software engineer with eight years of experience focused on Spark SQL and distributed data systems, currently contributing to Databricks' core Spark engine. An MSCS graduate from Stanford, she has a strong open-source footprint—fixing nuanced Spark SQL analyzer errors, ANSI-mode bugs, and improving Delta Lake test robustness in widely used projects like Apache Spark and Delta Lake. Her background includes internships at Google and Microsoft Research Asia and hands-on experience as a course assistant, reflecting both research depth and practical pedagogy. Based in Palo Alto, she combines backend engineering rigor with QA and test-automation expertise, often surfacing subtle correctness issues that improve reliability at scale.
8 years of coding experience
Bachelor of Science - BS Software Engineering, Bachelor of Science - BS Software Engineering at Shanghai Jiao Tong UniversityHigh School Diploma General Studies, High School Diploma General Studies at Suzhou High SchoolMaster of Science - MS Computer Science, Master of Science - MS Computer Science at Stanford University
Github Skills (14)
scala10
spark-sql10
big-data10
error-handling10
delta-lake10
sql10
testing10
java9
unit-testing9
javas9
spark8
data-analytics8
data-engineering8
acid8
Programming languages (3)
Github contributions (5)
apache/spark
Mar 2022 - Dec 2022
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:108 reviews, 8 commits, 31 PRs in 9 months
Contributions summary:Xinyi's contributions primarily involved modifying and enhancing the Apache Spark SQL engine. They worked on improving error messages in the Catalyst Analyzer, specifically grouping and standardizing exception messages. The user also addressed issues related to ANSI mode, fixing failing test cases in various suites such as ArithmeticExpressionSuite, AnalysisSuite, and others, by wrapping code blocks in conditional settings. Furthermore, they implemented features to handle implicit lateral column alias resolution.
analyticspythondata-processingsqlapache
delta-io/delta
Mar 2022 - Dec 2022
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:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:7 commits in 9 months
Contributions summary:Xinyi's contributions primarily involve modifying and refining existing test suites within the Delta Lake project. These changes focus on addressing test failures and improving error messages, particularly in scenarios involving ANSI mode and constraint validation. The user demonstrates expertise in identifying and resolving issues related to test execution, and ensuring accurate test coverage within the Delta framework. Their work includes adjusting test configurations and refactoring test code to address failures and ensure the robustness of the testing process.
analyticsprestodbflinkbig-dataspark
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