Daniel Tang

Daniel Tang is a skilled Data Engineer with extensive experience across multiple high-profile companies including Amazon, Facebook, Meta, Apple, and Bank of America. At Amazon, Daniel managed graphDB for employee access data and optimized ETL processes using AWS tools. Prior experience includes enhancing Talend pipelines at Bank of America, improving machine learning model accuracy, and establishing CI/CD practices. Daniel also worked with various data processing frameworks at other organizations, demonstrating strong capabilities in SQL, Python, and big data technologies. Educational background includes a degree in Finance and Biochemistry from Rutgers University.