Jack Moseley
Software Engineer at LinkedIn
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJack Moseley is a Software Engineer based in Sunnyvale, California with nine years of experience building robust back-end systems at LinkedIn. He specializes in data pipeline development and metadata-driven integrations, contributing to high-profile open-source work on Apache Gobblin where he implemented timestamp-based output splitting, GoldenGate envelope conversion, and Hive-driven compaction writers. Jack combines practical engineering with data serialization expertise (Avro) and a strong grounding in distributed data integration patterns. A University of Waterloo computer science graduate, he brings the discipline of a top CS program to solving large-scale ingestion and transformation challenges in production.
10 years of coding experience
Bachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at University of Waterloo
Github Skills (16)
javas10
deserialization10
avro10
data-serialization10
data-pipelines10
data-pipeline10
data-integration10
java10
data-engineering10
serialization10
hive9
apache9
data-transformation9
ingest8
replication7
Programming languages (1)
Github contributions (5)
apache/gobblin
Sep 2016 - Oct 2022
A distributed data integration framework that simplifies common aspects of big data integration such as data ingestion, replication, organization and lifecycle management for both streaming and batch data ecosystems.
Role in this project:
Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:131 reviews, 129 commits, 142 PRs in 6 years 2 months
Contributions summary:Jack contributed to the development of data integration functionalities, including creating a publisher for timestamp-based output splitting and building a converter for a GoldenGate envelope schema. They also worked on implementing a writer to launch compaction jobs utilizing Hive metadata. The contributions suggest a focus on data pipeline development, data transformation, and metadata management within the context of a data integration framework. They demonstrated experience with Avro schemas, data serialization/deserialization, and Hive integration.
big-datadata-ingestiondata-integrationreplicationdata
jack-moseley/gobblin
Sep 2016 - Jul 2023
Universal data ingestion framework for Hadoop.
Contributions:295 pushes, 119 branches in 6 years 11 months
data-ingestionbig-datasparkhadoopingestion
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