Technical VP - Big Data Platform

Huawei Technologies Canada Co., Ltd.; Markham; On-site; CAD 150,000 - 220,000; Full time

Job summary

A leading technology firm in Canada is seeking a Technical VP for their Computing Data Application Acceleration Lab. This role involves driving innovations in big data and AI, with responsibilities that include leading product development and assembling a top-tier research team. The ideal candidate will have a blend of deep technical knowledge and strong leadership skills, contributing actively to technological advancements while managing global teams.

Qualifications

• Deep understanding of big data engines like Spark and Flink.
• Hands-on experience in large model-oriented data engineering.
• Proven track record in architecture design with significant commercial impact.

Responsibilities

• Conduct in-depth analysis of technologies in the data domain.
• Develop AI big data technology strategies and roadmaps.
• Lead the team to deliver competitive data domain products.

Skills

Performance optimization

Data & AI solutions

Software-hardware co-design

Leadership across time zones

Job description

Huawei Canada has an immediate permanentopening for aTechnical 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 of mainstream products and advanced technologies in the data domain. Achieve groundbreaking innovations in big data engine, data-AI integration, large model data engineering, and software-hardware co-design on heterogeneous platforms. Explore the evolution direction of AI and big data, and drive the development of data and cutting-edge technologies.

• Develop comprehensive AI big data technology strategies and roadmaps, acting as a visionary in technical aspect to achieve commercial success. Lead the development of data domain products and build industry-leading big data + AI products to meet data processing requirements in the era of large models.

• Be responsible for attracting global talent and assembling a first-class research team. Lead the team to deliver competitive high-quality data domain products, ensuring the leading position in the market. As the director of the Big Data Committee, preside over major technical solution reviews and decision-making processes.

• Participate in big data industry and academic conferences or communities, and leverage open-source platforms/projects to enhance the influence of Kunpeng Architecture and its ecosystem in the big data domain.

About the ideal candidate：

• Deep understanding of core features and performance optimization of one of the main big data engines, such as Spark, Flink, Presto, HBase, Hive, etc.

• Deep understanding and hands-on experience in designing & developing solutions in the Data & AI domain. Rich experience in large model-oriented data engineering, and understanding of data requirements for large models.

• Proven experience in successful design, development, and delivery of software-hardware co-design projects involving CPU+GPU/NPU.

• Proven track record of architecture design and implementation in big data engines/databases solution, with remarkable commercial impact. Publication record in top-tier conferences or patents in the data domain is preferred. Experience in managing global R&D teams, and ability to effectively lead teams across time zones.

• This role is not solely a managerial position. The ideal candidate is expected to actively contribute to technical aspects, emphasizing a hands-on and leadership-oriented approach.

• Familiarity with ARM chips/ecosystems is an asset.

• Familiarity with Flink architecture and experience in self-developed engine development are assets.

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