Summary
Richard Ye is a data engineer with nine years of experience and a strong track record delivering large-scale, production-grade data systems across finance and healthcare. At IBM he architected ETL and migration pipelines that processed 10B+ rows and 50+ TB of data, achieving 100M rows/min throughput and driving multi‑million dollar contracts. He builds cloud-native, scalable architectures and production ML/AI services—from containerized YOLO inference on SageMaker to document and metadata pipelines that supported high concurrency. Comfortable across the stack, he reduces manual effort through tooling (e.g., MCP servers for ETL analysis) and modernizes legacy codebases to cut duplication and speed migrations. Now contributing as a Data Engineer at Stan while completing an MS in Computer Science at Georgia Tech, he pairs rigorous engineering with a practical flair for shipping impactful solutions. Outside work he blends technical obsession with active interests in sports and anime, reflecting an analytical yet creative problem-solving style.
10 years of coding experience