Jeremy Chung
Staff Infrastructure And Application Engineer
Taipei, Taiwan
Summary
👤
Senior🎓
Top SchoolJeremy Chung is a Staff Infrastructure and Application Engineer based in Taipei with 12 years building scalable backend systems, distributed architectures, and cloud-native platforms across networking, genomics, and security domains. He combines hands-on engineering leadership at Lookout and Ruckus with deep big-data expertise from roles that engineered Spark, Hadoop, and Elasticsearch pipelines to annotate hundreds of millions of genomic variants. Jeremy has contributed upstream fixes to Apache Spark—resolving SQL/JSON edge cases and JDBC array-type conversions—demonstrating attention to data correctness in large analytics engines. He blends algorithmic thinking (e.g., interval trees to speed genomic annotation) with production-grade system design to cut costs and latency, and is particularly adept at turning research-grade processing into reliable, cost-effective services.
12 years of coding experience
16 years of employment as a software developer
Master's degree, Management Information Systems, General, Master's degree, Management Information Systems, General at Chung Yuan Christian University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (13)
javas10
json10
apache-spark10
big-data10
jsonp10
sql10
jsonb10
java10
scala9
jdbc9
postgresql8
data-structure5
data-structures5
Programming languages (3)
Github contributions (5)
apache/spark
Oct 2017 - Oct 2017
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer / Database Engineer
Back-end Developer / Database EngineerContributions:1 commit, 9 PRs, 55 comments in 1 day
Contributions summary:Jeremy contributed to the Apache Spark project by addressing several SQL-related issues, particularly concerning the `json_tuple` function and data handling with JSON data. Their work included fixing a `NullPointerException` when handling null field names in `json_tuple`, ensuring consistent behavior with Hive regarding repeated columns, and handling corrupt records when creating DataFrames from JSON files. Additionally, they addressed a data type conversion issue, resolving a `ClassCastException` in the JDBC connector when reading data from PostgreSQL tables with array types such as `uuid[]`, `inet[]`, and `cidr[]`.
analyticspythondata-processingsqlapache
jmchung/swagger4javaee
Dec 2013 - Apr 2014
Contributions:5 commits in 3 months
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