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Cloud Native Data Engine team within Distributed Scheduling and Data Engine Lab, led by esteemed technical experts with extensive industry and academic experience, merge software development with cutting-edge industrial research in cloud database area. Our research currently focuses on cloud native database architecture and high-performance query and transaction processing (SQL Engine) in next-generation cloud infrastructure. Team publishes innovative research at leading conferences SIGMOD, VLDB, ICDE and recognized as key technology contributors in industry.
About the role :
Build and setup development tools and infrastructure.
Develop automation test framework and test tools.
Perform system testing for cloud, high availability and reliable database solution.
Write and review test cases and test specifications.
Develop problem determination solution for DBMS and drive toward root cause identification and resolution on cloud environment.
Work as part of a small buthigh-performance startup-like team mainly using C / C++ for development.
About ideal candidate :
Knowledge and experience in database and storage system structures and transaction processing; Proficient in UNIX scripting and Python programming.
Good understanding of database fundamentals, such as, transaction management, storage engine, MVCC, SQL optimization, recovery, HA.
Strong knowledge of SQL, C / C++ and Java, as well asstrong research capability and ability to learn new technologies / products quickly.
Good analytics skills; Ability to handle complex tasks by assessing issues and breaking down problems to reach an optimal solution.
Experience in different multiple database management systems like MySQL, PostgreSQL, Oracle, Db2, OceanBase and PolarDBis an asset.
Good understanding of cloud computing technologies, such as, cloud storage, distributed systems, parallel computations, consistency protocols, cloud computing and distributed system research background, such as having experience on Azure or AWSis an asset.
Experience in designing overall database system release QA plan,Linux administration and scripting languages, Docker, Virtual Machine and OpenStack is an asset.
Knowledge of Large Language Models (LLMs) and have experience of using Python, C / C++, Java and SQL in LLMs would be an asset.