Erik Krogen
Senior Staff Software Engineer at LinkedIn
California, United States
Summary
🤩
Rockstar🎓
Top SchoolErik Krogen is a Senior Staff Software Engineer with 11 years of experience designing and operating large-scale Big Data compute and storage systems, currently shaping Trino-based analytics infrastructure at LinkedIn. He combines hands-on backend engineering—contributions to Trino, Gobblin, Hadoop and Spark—with product-minded leadership focused on observability, cost efficiency, and user experience for offline compute. An Apache committer with a Berkeley CS/EE background, Erik has a track record of pragmatic fixes and feature work that improve reliability and developer ergonomics (for example adding Trino resource-group metrics and hardening HDFS ViewFS). He prefers solving human-centered problems as much as technical ones, aiming to make platforms easier to use and workplaces more inclusive. Colleagues rely on him to translate complex distributed-systems tradeoffs into roadmaps that deliver measurable value.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Science (BS), Master of Science (MS), Computer Science & Electrical Engineering, Bachelor of Science (BS), Master of Science (MS), Computer Science & Electrical Engineering at University of California, Berkeley
Stackoverflow
624reputation
15kreached
21answers
2questions
Github Skills (39)
hadoop-mapreduce10
apache-spark10
avro10
filesystem10
file-management10
data-pipelines10
query-builder10
testing10
big-data10
hdfs10
distributed-systems10
mapreduce10
hadoop10
resource-management10
java10
Programming languages (8)
Github contributions (5)
apache/hadoop
Oct 2016 - Sep 2022
Apache Hadoop
Role in this project:
Back-end Developer
Back-end DeveloperContributions:70 reviews, 238 commits, 23 PRs in 5 years 11 months
Contributions summary:Erik Krogen contributed to Hadoop, focusing on bug fixes and feature enhancements within the HDFS and ViewFS components. His work included resolving issues with DataNode software version counts during rolling upgrades, implementing optimizations for ViewFs listStatusIterator and listLocatedStatus, and handling exceptions in the StandbyCheckpointer and OIV ReverseXML Processor. His contributions are primarily in Java and relate to the core functionality of the Hadoop Distributed File System and View File System.
apachebig-datasparkhadoopjava
apache/spark
Jan 2021 - Oct 2021
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:Back-end Developer
Back-end DeveloperContributions:302 reviews, 8 commits, 34 PRs in 9 months
Contributions summary:Erik's primary contribution involves modifying and refactoring code related to the Apache Spark project. Their work includes removing references to potentially offensive terminology and improving error messages within the Avro module. The user also implemented changes to the YARN integration, including improvements to the display of driver log links and configuration options for the shuffle service. These contributions indicate a focus on enhancing code quality, usability, and system integration.
analyticspythondata-processingsqlapache
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