Career progression across AI, database engineering, and full-stack cloud systems.
“Kane(Eungchan) consistently delivered scalable systems with strong architectural thinking. His ability to optimize complex SQL workloads significantly improved production performance.”
“Eungchan approaches database engineering with deep understanding of execution plans and statistics engineering, and has consistently led resolution of critical client-side DB issues — from performance bottlenecks to unstable query plans and production-level incidents.”
Skills & Attribute
Languages for Front-end, Back-end, Data-modeling, Database, and Platform Engineering.
Filter by domain. All cards link to GitHub.
Embedded QuickSight analytics with snapshot automation and distributed scaling.
Multi-Organization real-time reporting platform with OLTP + Analytics separation.
SignalR + SQS + DynamoDB architecture for real-time delivery.
Azure → AWS distributed analytics architecture migration.
Application performance monitoring dashboard and operational insights.
Database statistics module & query optimizer improvement implementation.
Automated query optimization and tuning recommendations.
DB engine internals and system-level design experiments.
Edge-based object detection pipeline with real-time inference.
AI-based annotation & segmentation workflow.