Huawei Canada has an immediate permanent opening for a Database Research Expert.
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.
About the job:
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.
About the ideal candidate：
Expert proficiency in the kernel principles, storage engines, and query optimization of at least one mainstream database (e.g., PostgreSQL, MySQL, MongoDB, 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.