OLAP & Big Data Backend Intern

Shopee; Singapore; Vor Ort; SGD 20.000 - 33.000; Vollzeit

Zusammenfassung

Shopee's Data Infrastructure team is hiring a student intern to contribute to OLAP engines and the big data platform in Singapore. You will engage with Presto/Trino, ClickHouse, StarRocks, Druid, HBase, Milvus, graph or KV stores and help optimize performance, reliability, and scalability.

Work with product teams to translate requirements into features, document procedures, and explore AI-assisted approaches for troubleshooting and governance in a cloud-native Kubernetes environment.

Qualifikationen

• 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, 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.

Aufgaben

• 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, collaborating 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.

Kenntnisse

Java

C++

Go

Python

DS & algorithms

SQL

Ausbildung

Bachelor's degree or higher

Jobbeschreibung

Shopee's Data Infrastructure team is hiring a student intern to contribute to OLAP engines and the big data platform in Singapore. You will engage with Presto/Trino, ClickHouse, StarRocks, Druid, HBase, Milvus, graph or KV stores and help optimize performance, reliability, and scalability.

Work with product teams to translate requirements into features, document procedures, and explore AI-assisted approaches for troubleshooting and governance in a cloud-native Kubernetes environment.