Key Achievements

• Business Metrics Improvement: Participated in 24 service improvement experiments (A/B Tests) over 2 years, achieving ‘Total GMV per customer +1.04%’ (2020Q1), ‘Review submission rate +152%’ (2021Q2)
• Large-scale System Optimization: Improved Kafka consumer architecture in review domain, achieving 20x increase in message consumption speed, CPU usage reduction from 80% → 20% at peak, successfully processed 7 million Lag caused by incidents
• Security/Privacy Enhancement: Completed zero-downtime migration of PII anonymization/separation/deletion system across 145 tables, 581 APIs, 83 Batch Jobs, 29 Kafka Consumers without incidents

Security (Privacy Protection & Enhancement) Work

• Conducted privacy protection work to anonymize dormant/withdrawn member information and segregate or completely remove related data in review domain
• Surveyed all 145 tables and selected 72 tables requiring data separation
• Developed functionality to extract table features from ORM by analyzing Spring Data JPA, storing dormant member data in JSON format for separate storage
• Led 3 junior developers to apply Vault to 19 roles & OAuth2 to 7 roles

Review Domain Improvement & Performance Optimization

• Legacy Kafka Consumer Performance Optimization: Split one massive logic into 7 tasks, improved to distributed processing with 2 internal topics and 7 consumers
• Redis (Lettuce) Migration: Unified multiple cache infrastructures (Local Cache, Memcached, Elasticache Redis) used by review system
• API Latency Improvement: Achieved average 30% improvement through multi-threaded API calls, cache application, duplicate logic removal