Lim Kok Liang

Led the end-to-end development of a latency-sensitive crypto-trading system in Rust, including real-time market data ingestion via WebSocket for high-volume trading pairs, IPC-based data exchange between predictive models and the trading system to minimize latency, and the creation of a high-performance Rust monitoring library. Integrated QuestDB for fast time-series ingestion and Grafana for real-time visualization; implemented multi-threaded buffering to reduce operational overhead in latency-critical paths.

Led end-to-end development of a latency-sensitive crypto-trading system in Rust for production-grade performance. Engineered real-time market data ingestion pipelines via WebSocket APIs for high-volume crypto trading pairs, achieving sub-millisecond latency for order book and trade data. Implemented inter-process communication using shared memory to connect predictive models with the trading system, reducing inference-to-execution delay. Built a high-performance Rust monitoring library to capture low-level error and latency metrics. Integrated QuestDB for ultra-fast time-series ingestion and Grafana for real-time visualization, enabling precise performance diagnosis. Employed multi-threaded buffering to minimize overhead in latency-critical operations.

Led end-to-end migration of 5,000+ TB of production data across 150+ distributed NoSQL KV clusters (Abase1 → Abase2) with zero downtime; developed large-scale data migration strategies for complex data structures and high-throughput databases, addressing performance anomalies. Automated provisioning of virtual data centers across Abase clusters, significantly improving operational efficiency.