About the team:
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:
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Build and setup development tools and infrastructure.
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Develop automation test framework and test tools.
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Perform system testing for cloud, high availability and reliable database
solution.
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Write and review test cases and test specifications.
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Develop problem determination solution for DBMS and drive toward root cause
identification and resolution on cloud environment.
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Work as part of a small but high-performance startup-like team mainly using
C/C++ for development.
About ideal candidate:
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Knowledge and experience in database and storage system structures and
transaction processing; Proficient in UNIX scripting and Python programming.
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Good understanding of database fundamentals, such as, transaction management,
storage engine, MVCC, SQL optimization, recovery, HA.
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Strong knowledge of SQL, C/C++ and Java, as well as strong research
capability and ability to learn new technologies/products quickly.
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Good analytics skills; Ability to handle complex tasks by assessing issues
and breaking down problems to reach an optimal solution.
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Experience in different multiple database management systems like MySQL,
PostgreSQL, Oracle, Db2, OceanBase and PolarDB is an asset.
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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 AWS is an asset.
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Experience in designing overall database system release QA plan, Linux
administration and scripting languages, Docker, Virtual Machine and OpenStack
is an asset.
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Knowledge of Large Language Models (LLMs) and have experience of using
Python, C/C++, Java and SQL in LLMs would be an asset.
