Richard Startin
Oxford, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolRichard Startin is a JVM-focused software engineer with a decade of experience optimizing performance and observability across high-throughput systems. He has shipped production profiling and Java agent work at Datadog and StarTree, contributed performance-critical improvements to Apache Pinot, and holds commits in widely used open-source projects such as RoaringBitmap and Byte Buddy. Known for low-allocation, boundary-safe implementations and careful test coverage, he frequently tackles tricky JVM/bytecode and concurrency correctness issues that unblock customers and improve real-world reliability. Based in Oxford, he pairs an academic foundation in computer science and mathematics with hands-on systems work—from C++ JVM profilers to Java instrumentation—and has presented his profiling research at QCon, JFokus and p99conf. A less obvious strength is his knack for refactoring to reduce runtime allocations and memory churn, yielding measurable throughput and cost savings in production.
10 years of coding experience
6 years of employment as a software developer
BSc, Mathematics, BSc, Mathematics at University of YorkUniversity College London
Github Skills (33)
algorithm10
unit-testing10
json10
algorithms10
apache-pinot10
bitmap10
caching10
redis10
testing10
inverted-index10
data-serialization10
instrumentation10
roarr10
data-structure10
java10
Programming languages (14)
Github contributions (5)
DataDog/dd-trace-java
Apr 2020 - Jan 2023
Datadog APM client for Java
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 releases, 1915 reviews, 1586 commits in 2 years 9 months
Contributions summary:Richard's contributions primarily revolve around enhancing the Datadog APM client for Java, specifically focusing on the instrumentation of concurrent operations within the Java agent. They made changes to address cases of work stealing and prevent interference with adapter classes within the ForkJoinTask. The user also added unit tests to verify correct trace propagation within various executor types, and enhanced the robustness of the agent by fixing issues with rejected tasks and making adjustments for the proper capturing of thread migrations.
apm-clientapmbytebuddydatadoghqtracing
apache/pinot
Dec 2020 - Jan 2023
Apache Pinot - A realtime distributed OLAP datastore
Role in this project:Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:894 reviews, 137 commits, 225 PRs in 2 years 1 month
Contributions summary:Richard primarily focused on performance optimizations and efficiency improvements within the Apache Pinot datastore, as evidenced by commits related to inverted index creation and query performance. They improved query execution by utilizing more efficient APIs from RoaringBitmap for inverted indexes. Additional work was focused on reducing memory allocations and optimizing code paths for faster performance. These efforts spanned various components, including those related to data deserialization, dictionary lookups, and indexing.
realtimedata-streamolapapachedatastore
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