Shengkai Chen is a data and engineering leader with over 15 years in IT and a decade-plus focus on big data, BI/DW and machine learning, currently managing a 150-person data platform department in Guangzhou. He has led data product, platform and analytics initiatives across telecom, internet and finance—building recommendation systems, enterprise DWs and CRM solutions while also owning presales, bidding and budgeting. A hands-on contributor and Flink committer, he has improved JSON handling and performance in Apache Flink and Flink CDC, reflecting deep backend and streaming expertise. Comfortable from architecture to code, he combines Oracle/Teradata database optimization, Hadoop/Spark/Presto platforms and Python/R data mining with practical experience in .NET/J2EE and UNIX server environments. Known for bridging technical strategy and product delivery, he leverages long-standing telecom operator relationships to accelerate large-scale data programs.
8 years of coding experience
10 years of employment as a software developer
Bachelor, Majoring in Enterprise Administration, Bachelor, Majoring in Enterprise Administration at 安徽大学
Contributions:624 reviews, 136 commits, 322 PRs in 2 years 7 months
Contributions summary:Shengkai primarily contributed to improving the JSON format support within the Apache Flink project. They addressed timestamp format inconsistencies by modifying code related to JSON serialization and deserialization, ensuring compliance with SQL standards and adding a configuration option for fallback. These changes involved updating Java files, focusing on the flink-json module, and included test cases to validate the new format. Further contributions involved fixing bugs and ensuring resource management for JDBC connectors.
Contributions:13 reviews, 1 commit, 7 PRs in 1 day
Contributions summary:Shengkai contributed to the Flink CDC project by addressing code-related issues and improving the system's overall performance and stability. They added support for newer JDK versions, resolving compatibility problems. The user also fixed a memory-related issue within the schema history, which likely optimized data processing. Furthermore, they modified metrics to ensure the accuracy of the delay times during different phases of the data pipeline.
flinkchange-data-captureapachebig-dataspark
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.