Seungchul Lee
Nexon, Senior Data Engineer, Software Engineer, Streaming, Data Lakehouse
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Seungchul Lee is a software engineer at Nexon, working with data from a wide range of sources in cloud-based data platforms. His interests have evolved from stream processing with Apache Flink to lakehouse architectures, focusing on how data is stored and efficiently served at scale. Before joining Nexon, he worked on processing sensor data on large-scale Spark data pipelines in the manufacturing domain. He has presented his work at multiple technical conferences, including Spark Summit.
CDC Pipelines on Iceberg: When Theory Meets Production Workloads
Change Data Capture (CDC) has become essential for moving data from transactional systems into lakehouse architectures. Apache Iceberg is increasingly adopted for this purpose, but teams often find it challenging to understand how Iceberg behaves in real CDC pipelines.
This session shares lessons learned from running CDC pipelines built on Apache Iceberg at scale at Nexon. We focus on common production scenarios and how they were addressed: how CDC pipelines behave under burst traffic and where bottlenecks emerge, how update and delete-heavy workloads require different handling than insert-only cases, and how design choices such as primary key handling and partitioning can lead to data duplication and operational overhead.
This talk bridges Iceberg concepts with production realities through CDC use cases.
Seungchul Lee
Nexon, Senior Data Engineer, Software Engineer, Streaming, Data Lakehouse
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