Huawei Canada has an immediate permanent opening for a Lead Database Engineer - Distributed Data Systems.
About the team:
The Distributed Data Storage and Management Lab leads research in distributed data systems, aiming to develop next-generation cloud serverless products that encompass core infrastructure and databases. This lab addresses various data challenges, including cloud-native disaggregated databases, pay-by-query user models, and optimizing low-level data transfers via RDMA. Teams within this lab create advanced cloud serverless data infrastructure and implement cutting-edge networking technologies for Huawei's global AI infrastructure.
About the job:
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Lead the design and development of a cutting-edge, all-in-one cloud-native database system.
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Architect a system that can handle diverse workloads, including OLTP, OLAP, HTAP, large-scale OLAP, and AI-native workloads such as LLMs and vector retrieval.
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Ensure the system's capability to handle AI jobs and provide flexible scalability.
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Develop an infrastructure that allows for the seamless integration of different databases.
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Oversee the foundational architecture for upper data processing.
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Collaborate with cross-functional teams to ensure alignment with company goals and objectives.
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Provide technical leadership and mentorship to the engineering team.
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Stay up-to-date with industry trends and advancements to drive continuous innovation.
About the ideal candidate:
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Minimum of 10 years of experience in database development and architecture.
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Proven experience in leading large-scale database projects in well-known companies.
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Proficiency in C , Linux, parallel computing, MySQL, PostgreSQL, AI and distributed systems.
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Strong understanding of cloud-native architectures and database systems.
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Demonstrated ability to design systems that handle multiple workloads efficiently.
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Excellent problem-solving skills and a proactive approach to addressing challenges.
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Strong communication and leadership skills with the ability to inspire and guide a team.
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Experience with AI-native workloads and machine learning integrations is an asset.
