Internship with Shopee's data infrastructure team in Singapore to develop, optimize and maintain OLAP/Big Data engines such as Presto/Trino, ClickHouse, StarRocks, Druid, HBase and Milvus. Day-to-day work includes performance tuning, troubleshooting, running engines on Kubernetes and exploring AI/LLM tooling, using Java, C++, Go or Python.
Job Description:
Participate in the development, optimization and maintenance of our OLAP and Big Data engines and platform, focusing on one of them: Presto/Trino, ClickHouse, StarRocks, Druid, HBase, Milvus, graph or KV store.
Engage in system performance tuning and troubleshooting, ensuring service stability and high availability.
Analyze and solve user problems combining user scenarios, and collaborate with the product team to develop and optimize features based on business requirements.
Contribute to running the engines on Kubernetes, and explore using AI / LLMs to solve complex problems in troubleshooting and governance.
Write and maintain related technical documentation and SOPs.
Requirements:
Pursuing a bachelor's degree or above in Computer Science, Engineering, or related fields.
Proficient in Java (or C++, Go or Python), with a solid foundation in data structures and algorithms.
Basic understanding of Big Data / OLAP components and their internal mechanisms (HDFS, Presto/Trino, ClickHouse, Druid, HBase, etc), and comfortable with SQL.
Excellent team collaboration and communication skills, able to respond and resolve issues promptly.
Experience with OLAP technologies and data modeling is highly desirable.
Good To Have:
Previous coursework, projects or internships in the Big Data or database domain.
An interest in cloud-native technologies, including Kubernetes.
Interest in open-source contributions and eagerness to learn from the open-source community.
Interest in using AI to solve complex engineering problems.