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:
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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.
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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.
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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.
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Develop the database technology roadmap, guide the team in overcoming key
technical challenges, and build our industry-leading technical influence.
About the ideal candidate：
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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.
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Solid programming foundation in C/C++, proficiency in Linux systems
programming, experiences with software-hardware co-design and optimization.
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Knowledge of modern computer architecture and familiarity with emerging
technologies such as CXL, RDMA, and NVMe-oF is an asset.
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Familiarity with the big data technology ecosystem (Hadoop, Spark, Flink,
Lakehouse, unified batch/stream processing, etc.) is an asset.
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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.
