Job description
Huawei Canada has an immediate permanent opening for a Lead Database Engineer & Architect.
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:
Lead the design and development of a cutting-edge, all-in-one cloud-native database system.
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.
Ensure the system's capability to handle AI jobs and provide flexible scalability.
Develop an infrastructure that allows for the seamless integration of different databases.
Oversee the foundational architecture for upper data processing.
Collaborate with cross-functional teams to ensure alignment with company goals and objectives.
Provide technical leadership and mentorship to the engineering team.
Stay up-to-date with industry trends and advancements to drive continuous innovation.
Job requirements
About the ideal candidate:
Minimum of 10 years of experience in database development and architecture.
Proven experience in leading large-scale database projects in well-known companies.
Proficiency in C++, Linux, parallel computing, MySQL, PostgreSQL, AI and distributed systems.
Strong understanding of cloud-native architectures and database systems.
Demonstrated ability to design systems that handle multiple workloads efficiently.
Excellent problem-solving skills and a proactive approach to addressing challenges.
Strong communication and leadership skills with the ability to inspire and guide a team.
Experience with AI-native workloads and machine learning integrations is an asset.
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