About

Allen Tang is a highly skilled software engineer with over 9 years of experience in various technologies. Currently working at Spotify, he has gained expertise in designing and implementing real-time processing systems using Kafka and Storm. At Wayfair, Allen played a key role in refactoring warehouse receipts processing from batch to real-time using Kafka, PHP, and Storm. He also designed and implemented a mod of Confluent's Kafka Connect JDBC library, enabling internal customers at Wayfair to poll SQL Server changetracking data to generate streaming data in Kafka for real-time processes to consume from for stream processing and data ingestion into other data stores. Allen has provisioned an internal instance of Kafka Connect, called Sayl, that is integrated into Wayfair's build/release management infrastructure to make it possible for internal customizations to be made on top of open-source offerings. He has also worked with engineering leadership to establish a new team in infrastructure to grow Sayl, becoming the first member within "Emerging Systems," a team purposed with promoting event-driven solutions via Kafka, Sayl (Kafka Connect), and more. Prior to joining Spotify and Wayfair, Allen worked for Cambridge Systematics, where he worked on government-contracted projects such as the Metropolitan Transportation Authority's Bus Time app (OneBusAway-NYC) and Sound Transit's OneBusAway-ST. He has also worked on Oklahoma's DOT/DPS OKiePROS, an online permitting system that facilitates the process of issuing permits to the trucking industry. Allen holds a Bachelor's degree in Computer Science from the University of Massachusetts and has experience with a wide range of technologies, including Kafka, PHP, SQL, mobile, frontend, big data, Javascript, web, Java, test, search, UI, backend, and Ruby. With his relevant experience and expertise, Allen is a valuable asset to any software engineering team.