Database Research Expert - Big Data Platform

About the team:

The Computing Data Application Acceleration Lab aims to create a leading global data analytics platform organized into three specialized teams using innovative programming technologies. This team focuses on full-stack innovations, including software-hardware co-design and optimizing data efficiency at both the storage and runtime layers. This team also develops next-generation GPU architecture for gaming, cloud rendering, VR/AR, and Metaverse applications.

One of the goals of this lab are to enhance algorithm performance and training efficiency across industries, fostering long-term competitiveness.

• Lead the core architecture design and evolution of our next-generation data analytics infrastructure, with a focus on high-performance, scalable databases and big data analytics systems.

• Spearhead in-depth performance analysis and optimization of the database kernel, resolving extreme performance bottlenecks under massive data loads to enhance system efficiency and stability.

• Track and research cutting-edge technologies in databases, data analytics, and the integration of AI; lead exploratory projects, especially on innovative database solutions leveraging software-hardware co-design, such as computation and storage decoupling and CXL-based memory pooling.

• Develop the database technology roadmap, guide the team in overcoming key technical challenges, and build our industry-leading technical influence.

• Expert proficiency in the kernel principles, storage engines, and query optimization of at least one mainstream database (e.g., Postgre
  
  SQL, MySQL, Mongo
  
  DB, DB2, Oracle DB, etc.), with hands-on experience in source-code level development and/or deep optimization.

• Solid programming foundation in C/C++, proficiency in Linux systems programming, experiences with software-hardware co-design and optimization.

• Knowledge of modern computer architecture and familiarity with emerging technologies such as CXL, RDMA, and NVMe-oF is an asset.

• Familiarity with the big data technology ecosystem (Hadoop, Spark, Flink, Lakehouse, unified batch/stream processing, etc.) is an asset.

• Possessing excellent technical vision, strong learning abilities, and complex problem-solving skills. Keen insight into cutting-edge database and data analytics technologies (e.g., AI for DB, vector databases), coupled with the passion and capability to apply new technologies to real-world scenarios.