Technical VP - Big Data Platform

Huawei Canada has an immediate permanent opening for a Technical VP.

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:

• Conduct in-depth analysis and gain insights into mainstream products and advanced technologies in the data domain. Lead core technological breakthroughs and innovation in areas including big data engines, databases, data-AI integration, data engineering for large models, and hardware-software co-design for heterogeneous platforms. Explore the evolving direction of AI and big data/database, driving the advancement of cutting-edge technologies.
• Formulate a comprehensive "Data+AI" technology strategy and roadmap, acting as a technical visionary on projects to ensure commercial success. Lead the development of data-domain products, creating industry-leading Data+AI solutions to meet the data processing demands of the large model era.
• Attract top global talent in the data domain to build a world-class research team. Lead the team to deliver high-quality, competitive products, ensuring the leading position in the market. Serve as the Chair of the Big Data Committee, presiding over major technical design reviews and the decision-making process.
• Engage with the big data industry and academic communities through conferences and other forums. Leverage open-source platforms and projects to enhance the influence of the Kunpeng architecture and its ecosystem in the AI and big data landscape.

About the ideal candidate：

• In-depth understanding of the architecture and performance optimization of at least one major big data engines, such as Spark, Flink, Presto, HBase, or Hive.
• Familiarity with the principle of databases like PostgreSQL and MySQL, with a profound understanding of distributed database architectures such as Shared-Nothing and Shared-Everything.
• Deep understanding of the Data & AI domain with proven experience in design and development. Extensive experience in data engineering tailored for large models, knowing the specific data requirements.
• Proven track record of successfully designing, developing, and delivering solutions involving hardware-software co-design for CPU + GPU/NPU environments.
• Demonstrated contributions to architectural design and implementation of big data engine/database solutions, with remarkable commercial impact. Publications in top-tier conferences or patents in the big data field are preferred.
• Proven experience in managing global R&D teams and leading them effectively across different time zones.
• Familiarity with the ARM chipset and ecosystem is an asset.