Responsibilities: 1. Design and build a distributed real-time data warehouse architecture, maintain its stability and data quality, and ensure system resilience under extreme market conditions (e.g., rapid Bitcoin price fluctuations). 2. Collect, cleanse, and store real-time trading data from exchanges, supporting processing volumes of millions of transactions per second. 3. Lead the development of real-time and offline CDP platforms, real-time user tagging, online real-time metrics, real-time risk control systems, and abnormal trading behavior monitoring. 4. Optimize data warehouse performance, reduce consumption latency, and design multi-cloud, multi-region high-availability solutions to ensure production uptime. Requirements: • Solid programming fundamentals and proficiency in Java • Expert in Apache Flink, including Flink SQL and Streaming internals; familiar with connector implementations and experienced in large-scale real-time data warehouse projects • Experience with Flink integrated with data lakes (e.g., Apache Paimon) • Understanding of common upstream and downstream Flink connector storage system architectures • Experience in real-time data quality management • Proficient with other big data ecosystem components such as StarRocks, HBase, Kafka, Elasticsearch, etc. • Prior experience building on-chain data warehouses is a plus Note: This role will later transition to Hong Kong. A relocation subsidy is provided, and the company will handle applications under the Hong Kong Quality Migrant Admission Scheme.