Chamikara Jayalath
Senior Software Engineer at Google
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolChamikara Jayalath is a Senior Software Engineer based in San Jose with 21 years of experience building massively scalable, geo-distributed data systems and large-scale data processing pipelines. At Google since 2014, he works on production-grade data processing and analysis, applying research-driven approaches from his PhD in computer science to real-world systems. An active open-source contributor, he has made notable backend improvements to Apache Beam and Google Cloud Dataflow SDK—enhancing file-based source size estimation, GCS path handling, and performance-critical readers. Known for practical engineering rigor, he combines deep academic training with hands-on bug fixes and refactors that improve reliability and testability at scale.
21 years of coding experience
Bachelor of Engineering (B.Eng.), Computer Science and Engineering, GPA 3.96, Bachelor of Engineering (B.Eng.), Computer Science and Engineering, GPA 3.96 at University of MoratuwaDoctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at Purdue University
English, Sinhalese
Github Skills (13)
google-cloud-storage10
javas10
google-cloud-dataflow10
data-pipeline10
data-pipelines10
apache-beam10
python10
java10
data-processing10
testing10
unit-test7
avro6
gcp5
Programming languages (4)
Github contributions (5)
apache/beam
Feb 2016 - Jan 2023
Apache Beam is a unified programming model for Batch and Streaming data processing.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 releases, 1003 reviews, 858 commits in 7 years
Contributions summary:Chamikara made significant contributions related to improving data processing capabilities within the Apache Beam project. They focused on enhancing size estimation for file-based sources, including updating the `FileBasedSource`, `Dataflow runner`, and adding corresponding unit tests. The user also addressed bug fixes in the `avroio_test` file, specifically resolving issues related to file corruption. Additionally, the user addressed performance improvements in various areas by implementing better code handling in different areas.
golangpythonstreaming-databeambatch
GoogleCloudPlatform/DataflowJavaSDK
Jan 2015 - Dec 2015
Google Cloud Dataflow provides a simple, powerful model for building both batch and streaming parallel data processing pipelines.
Role in this project:Back-end Developer
Back-end DeveloperContributions:34 commits, 1 comment in 11 months
Contributions summary:Chamikara primarily focused on improving the Google Cloud Dataflow Java SDK, specifically enhancing Google Cloud Storage (GCS) path handling and file pattern expansion. Their contributions involved refactoring wildcard matching logic, adding support for range patterns, and fixing issues related to directory handling. They also improved the Datastore integration, making it more adaptable for testing and updated the DataStoreWordCount example. In addition, the user modified the internal reader and source objects to facilitate more flexible and efficient data ingestion processes, as well as several bug fixes.
stream-processingbeambatchdata-processingparallel
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