Chaochen Qian
Member Of Technical Staff at Trent AI
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolChaochen Qian is a seasoned backend engineer and technical lead with over a decade of experience building large-scale, data-intensive systems; he helped found and launch Amazon Data Firehose and scaled it to process petabytes per day. Based in Sunnyvale, he brings deep expertise in Java/J2EE, distributed streaming, database replication, and DevOps automation, having led integrations across Kinesis, Kafka/MSK, S3, Iceberg, Redshift and OpenSearch. His open-source contributions include reliability and error-handling improvements to the widely used Amazon Kinesis Agent, demonstrating a focus on operational robustness in real-time pipelines. Trained at Carnegie Mellon and Fudan, Chaochen blends academic rigor with hands-on product delivery and an ability to convert complex data flow requirements into production-ready, maintainable systems.
10 years of coding experience
14 years of employment as a software developer
Bachelor of Science, Computer Science, Bachelor of Science, Computer Science at Fudan UniversityMaster's degree, Information Systems Management, Master's degree, Information Systems Management at Carnegie Mellon University
Github Skills (9)
javas10
amazon-kinesis10
error-handling10
aws10
kin10
java10
logging9
data-conversion9
testing8
Programming languages (2)
Github contributions (5)
awslabs/amazon-kinesis-agent
Nov 2015 - Jan 2020
Continuously monitors a set of log files and sends new data to the Amazon Kinesis Stream and Amazon Kinesis Firehose in near-real-time.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:13 releases, 6 reviews, 19 commits in 4 years 3 months
Contributions summary:Chaochen contributed to the Amazon Kinesis Agent, releasing and updating various versions of the software. Their work included bug fixes and enhancements, such as enabling retriable error messages. Code modifications involved changes to core components like `FirehoseSender`, `KinesisSender`, and `AbstractParser`, indicating a focus on improving the agent's reliability and error handling capabilities. The user also addressed issues related to checkpointing and data conversion, enhancing the overall stability and functionality of the agent.
amazon-kinesislogfile
chaochenq/software-agent-sdk
Jun 2026 - Jun 2026
Contributions:2 pushes in 1 day
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