Andrew Xue
Member Of Technical Staff at Genmo
Old Toronto, Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolAndrew Xue is a backend-focused software engineer and Member of Technical Staff with eight years of hands-on experience and ongoing CS studies at the University of Waterloo. He has interned at Databricks, Snowflake, Sentry, Anyscale and others, shipping features that improve observability and alerting in production systems. As an active open-source contributor, he has added metrics, observability, and documentation improvements to high-profile projects like Ray and Sentry, demonstrating a knack for making distributed data pipelines and alert systems more transparent and reliable. His work often targets operator-level metrics and data integrity—small changes that yield outsized debugging and performance benefits. Based in Toronto, he’s now applying that backend expertise at Genmo while still seeking internship-level opportunities that emphasize scalable systems and measurable impact. Colleagues describe him as detail-oriented with a pragmatic focus on observability and end-to-end data correctness.
8 years of coding experience
2 years of employment as a software developer
Bachelor of Computer Science, Computer Science, Bachelor of Computer Science, Computer Science at University of Waterloo
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (25)
data-pipelines10
python10
django10
data-engineering10
alertdialog10
event-driven-architecture10
alertview10
alerts10
rule-engine10
performance-optimization10
rule-based10
ray10
data-pipeline10
data-science9
postgresql9
Programming languages (5)
Github contributions (5)
getsentry/sentry
Sep 2022 - Dec 2022
Developer-first error tracking and performance monitoring
Role in this project:
Back-end Developer
Back-end DeveloperContributions:96 reviews, 72 commits, 112 PRs in 2 months
Contributions summary:Andrew's commits primarily focused on enhancing the alert email functionality and the issue alert feature within the Sentry platform. They implemented timezone conversions for alert email datetimes and introduced event ID recording in RuleFireHistory for better issue alert tracking. Furthermore, the user contributed to the development of rule previews, adding support for regression, reappearance, and event-level filters to create a more informative user experience. These contributions suggest a focus on improving the core alert system.
performance-monitoringcrash-reportingcrash-reportserror-monitoringmonitoring
ray-project/ray
Sep 2023 - Dec 2023
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Role in this project:Back-end Developer
Back-end DeveloperContributions:91 reviews, 71 PRs, 38 pushes in 3 months
Contributions summary:Andrew primarily contributed to the Ray data project by implementing features and improving the performance of data processing pipelines. Their work included storing and reporting bytes spilled/restored after plan execution, enhancing dataset metrics, and adding operator-level metrics for better observability. They also linked dataset IDs in the constructor and corrected metrics identifiers for the `materialize` function, ensuring data integrity. Furthermore, the user updated and added documentation to the data dashboard.
aimachine-learningraydistributedparallel
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.