Supports the design and development of scalable end-to-end data pipelines and cloud data platforms. Responsibilities include improving data reliability and quality, implementing data management practices, supporting automation and process improvements, ensuring secure and cost-effective solutions, and recommending system enhancements. The intern collaborates with global teams and gains hands-on experience in data engineering, project coordination, and innovation management.
Overview
We are looking for a dynamic and proactive intern to join our team. This role will support day-to-day tasks, offering hands-on experience in managing and executing strategic projects. The intern will collaborate closely with the Manager, providing valuable assistance in areas such as process improvement, research, project coordination, and automation.
QualificationsTechnical:
- Understanding of RDBMS or NoSQL databases
- Experience in building ELT/ETL pipelines (preferred)
- Scripting skills in Python, Spark, and SQL (preferred)
- Familiarity with data analytics and visualization tools (e.g., Power BI)
Non-Technical:
- Proficient in English and Mandarin
- Able to work independently and in global teams
- Strong commitment to service excellence
- Good communication, planning, and analytical skills
- Eager to learn and apply new technologies
Benefits:
- Gain hands-on experience in innovation management, project coordination, and automation implementation.
- Opportunity to work closely with industry professionals and contribute to real-world projects.
- Work in a multicultural, multilingual environment, enhancing cross-cultural communication skills.
- Potential to network within the industry
- Work with the team to design and build scalable end to end data pipelines from multiple sources and system.
- Drive the technical design and implementation of large scale data platforms, utilizing modern technologies in a cloud environment
- Ability to provide cost effective, secure and scalable solution which is operationally efficient
- Develop and implement methods to improve data reliability & quality
- Implement and manage company data management practices and policies
- Proactively and regularly make recommendations for system improvements
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