Data Engineering Intern: Build Scalable Pipelines

rednote; Singapore; On-site; SGD 11,000 - 18,000; Part time

Job summary

rednote is offering a regular internship for current Singapore university students. The internship is project-based and lasts three months or longer, with opportunities to join the International Data Warehouse Team in designing, building, and maintaining data platforms.

You will collaborate with product managers, data scientists/analysts, software and ML engineers, and other stakeholders to understand data needs and deliver data solutions.

Qualifications

• Currently pursuing a Bachelor’s degree or above, preferably in computing or a related field.
• Coursework or equivalent knowledge in SQL, Data Structures and Algorithms.
• Basic proficiency in at least one programming language.
• Proficiency in Mandarin Chinese, with the ability to communicate effectively in professional settings.

Responsibilities

• Work closely with product managers, data scientists/analysts, software and machine learning engineers, and other stakeholders to understand data requirements and deliver data solutions that meet business needs.
• Evaluate, implement, and maintain data infrastructure tools and technologies to support efficient data processing, storage, and querying.
• Design, build, and optimize scalable data pipelines to ingest, process, and transform large volumes of data.
• Design and implement insightful data visualization solutions for analytical reporting.
• Continuously optimize data pipelines, queries, and workflows to improve performance, reduce latency, and enhance scalability.

Skills

Mandarin Chinese

Strong communication

Team collaboration

Education

Bachelor’s degree or above in computing or related field

Tools

SQL

Python

Job description

rednote is offering a regular internship for current Singapore university students. The internship is project-based and lasts three months or longer, with opportunities to join the International Data Warehouse Team in designing, building, and maintaining data platforms.

You will collaborate with product managers, data scientists/analysts, software and ML engineers, and other stakeholders to understand data needs and deliver data solutions.