Sam Whittle
Senior Staff Software Engineer at Google
Oslo, Norway
Summary
🤩
Rockstar🎓
Top SchoolSam Whittle is a Senior Staff Software Engineer based in Oslo with 11 years of experience designing and shipping large-scale streaming data systems at Google, where he currently leads Cloud Dataflow Streaming. He combines deep systems engineering—work that traces back to MillWheel—with hands-on contributions to high-profile open-source projects like Apache Beam and the Dataflow Java SDK, focusing on state prefetching, timer refactors, and stability/performance improvements. Known for pragmatic optimizations that reduce latency and improve reliability in real-time pipelines, he blends low-level backend improvements with operational leadership. Sam holds a BS in Computer Science and Mathematics from the University of Washington and brings a rare mix of long-term product ownership and active open-source craftsmanship to distributed stream processing.
11 years of coding experience
15 years of employment as a software developer
BS Computer Science Mathematics, BS Computer Science Mathematics at University of Washington
English
Stackoverflow
51reputation
4kreached
1answer
9questions
Github Skills (26)
data-stream10
dataflow-programming10
dataflow10
java10
stream10
javas10
data-streaming10
performance-optimization10
data-processing10
state-management10
stream-processing10
apache-beam10
streaming-data10
streaming10
testing9
Programming languages (3)
Github contributions (5)
apache/beam
Nov 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:742 reviews, 93 commits, 380 PRs in 6 years 2 months
Contributions summary:Sam's primary contributions focus on improving the `ReduceFnRunner` within the Apache Beam project, specifically concentrating on enhancing prefetching mechanisms to optimize state management and trigger execution. Their work includes adding new prefetch methods, refactoring the existing timer logic, and introducing a batched onTimers method. Additionally, the user addressed issues with late data handling, including a fix for dropping data in the processing pipeline, and made improvements to the Debezium module.
golangpythonstreaming-databeambatch
GoogleCloudPlatform/DataflowJavaSDK
Feb 2015 - 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:14 commits, 2 PRs, 1 comment in 1 year 10 months
Contributions summary:Sam primarily focused on enhancing the Dataflow Java SDK's backend functionality and improving its performance. Their contributions involved implementing features like reporting statistics responses, fixing infinite retries in streaming mode, and optimizing counter processing. Furthermore, they made improvements to the streaming worker's progress updates and optimized code related to state prefetching. Their work centered on increasing the stability and efficiency of the SDK.
stream-processingbeambatchdata-processingparallel
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