Mark Liu
Software Engineer at Google
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolMark Liu is a software engineer with 13 years of experience, currently at Google in the San Francisco Bay Area, focused on building reliable, testable data-processing systems. He is an Apache Beam committer and has strengthened Beam’s Python SDK with integration tests and verification tools while also contributing Beam-focused benchmarks to GoogleCloudPlatform/PerfKitBenchmarker. His background spans performance-sensitive C++ systems—authoring a multithreaded computer vision simulation at Qualcomm—to front-end work early in his career, giving him full-stack fluency. A Georgia Tech MS and UC San Diego dual-degree alumnus, he combines strong academic grounding with practical open-source impact on cloud benchmarking and stream/batch processing.
13 years of coding experience
3 years of employment as a software developer
IGETC, General Education, IGETC, General Education at Norco CollegeUniversity of California, San DiegoHigh School, A-G General Education, High School, A-G General Education at Eleanor Roosevelt High SchoolMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at Georgia Institute of TechnologyHigh School, A-G General Education, High School, A-G General Education at JFK Middle College High School
Chinese, English
Github Skills (17)
gradle10
dataflow-programming10
dataflow10
python10
testing10
test-framework10
gradlew10
apache-beam10
integration-testing10
test-automation10
gcp9
pubsub8
google-cloud-pubsub8
devops8
java7
Programming languages (5)
Github contributions (5)
apache/beam
Dec 2016 - Nov 2019
Apache Beam is a unified programming model for Batch and Streaming data processing.
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:1 release, 188 commits, 308 PRs in 2 years 11 months
Contributions summary:Mark primarily focused on enhancing the testing framework for the Apache Beam project, particularly for the Python SDK. Their contributions included developing new end-to-end tests, improving existing test infrastructure, and adding new verifiers, like file checksum verification and PubSub message verification. The changes included the implementation of new integration tests and the correction of existing tests, highlighting their focus on ensuring the reliability and correctness of the Apache Beam library.
golangpythonstreaming-databeambatch
GoogleCloudPlatform/PerfKitBenchmarker
May 2017 - Jun 2019
PerfKit Benchmarker (PKB) contains a set of benchmarks to measure and compare cloud offerings. The benchmarks use default settings to reflect what most users will see. PerfKit Benchmarker is licensed under the Apache 2 license terms. Please make sure to read, understand and agree to the terms of the LICENSE and CONTRIBUTING files before proceeding.
Role in this project:Backend & DevOps Engineer
Backend & DevOps EngineerContributions:9 commits, 10 PRs, 14 comments in 2 years 1 month
Contributions summary:Mark primarily contributed to the Beam integration benchmark within the PerfKit Benchmarker repository. They implemented support for Beam Python, increasing the repo build timeout, and fixing errors in the Beam repo initialization. The user's work also involved Gradle configurations for running Python benchmarks and improving benchmark logging. They also fixed issues with the Beam Gradle command for Java and made other minor corrections to existing benchmarks.
license-2licensedbenchmarkingapache-license-2pkb
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