Scott Wegner
Staff Software Engineer at Google
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolScott Wegner is a Staff Software Engineer in Seattle with 13 years of experience building large-scale cloud and big-data systems at Google and Microsoft. He specializes in distributed data processing, contributing to core projects like Apache Beam and Google Cloud Dataflow and improving robustness around aggregators, resource management, and metadata for production pipelines. His work on TensorFlow documentation and TensorFlow Federated shows a rare blend of backend engineering, technical writing, and applied ML knowledge, including practical examples for decentralized analytics. At Microsoft he helped build experimentation and analysis platforms and earlier contributed to abuse-detection and cloud testing infrastructure, demonstrating full lifecycle ownership from research to production. Known for pragmatic refactors and improving error handling in critical SDKs, he combines deep Java expertise with cloud-native operational experience.
13 years of coding experience
9 years of employment as a software developer
University of Illinois Urbana-Champaign
Spanish, English
Stackoverflow
7,383reputation
782kreached
90answers
22questions
azure-devops
top-5%
moq
top-5%
linq
top-5%
ref
top-1%
tfs
top-5%
Github Skills (34)
parserator10
parser10
python10
machine-learning10
java10
javas10
ref10
tensorflow10
exception-handling10
apache-beam10
api-generator10
documentation10
apigen10
linq9
testing9
Programming languages (15)
Github contributions (5)
GoogleCloudPlatform/DataflowJavaSDK
Feb 2016 - Dec 2016
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:64 commits, 24 PRs, 48 comments in 10 months
Contributions summary:Scott focused on improving the Dataflow Java SDK, specifically addressing aggregator creation and exception handling within the `DoFn` and `ParDo` transforms. The user implemented validation to prevent incorrect aggregator usage during pipeline execution and ensured system exceptions were not unnecessarily wrapped. They also refactored code to utilize "try-with-resources" for resource management and updated the codebase to support DisplayData for several key IO and transform implementations.
stream-processingbeambatchdata-processingparallel
apache/beam
Feb 2016 - Feb 2019
Apache Beam is a unified programming model for Batch and Streaming data processing.
Role in this project:Back-end Developer
Back-end DeveloperContributions:479 commits, 415 PRs, 161 pushes in 3 years
Contributions summary:Scott primarily contributed to the internal workings of the Apache Beam Java SDK. Their focus was on enhancing the `DisplayData` class by adding new metadata, fixing issues related to the handling of sub-components and namespaces. They also worked on various code improvements such as removing redundant imports and adding checkstyle checks. The user demonstrated a solid understanding of Java and the core design of the SDK.
golangpythonstreaming-databeambatch
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