Data Engineer

As a Data Engineer at Cube Asia, you will use various methods to transform raw data into useful data systems. You’ll strive for efficiency by aligning data systems with business goals.

To succeed in this position, you should have prior experience in large-scale public data collection from the web using open APIs and other tools, as well as a good understanding of the terms and guidelines, as well as the technical considerations, governing such data collection.

Data engineer skills also include familiarity with several programming languages and a basic knowledge of machine learning methods. If you are detail-oriented, with excellent organizational skills and experience in this field, we’d like to hear from you.

Responsibilities

• Build and maintain scalable data pipelines to process and integrate e-commerce data from multiple sources.
• Design and implement a modern cloud-based data lakehouse architecture using AWS services such as S3, Athena, Glue, Fargate, and Iceberg
• Explore tools and solutions for high-performance data transformation and analysis, such as Polars, DuckDB, and PySpark.
• Work with data analysts to deliver accessible and well-structured datasets for reporting and advanced analytics.
• Collaborate architects on designing data platforms.
• Explore ways to enhance data quality and reliability

What You’ll Love About This Role

• Build from Scratch: Be part of a team creating foundational data systems and processes, shaping the future of our platform.
• Learn by Doing: Gain hands-on experience working with modern tools, cloud technologies, and real-world data challenges.
• Work on Complex Projects: Tackle exciting and challenging problems, from integrating large-scale e-commerce data to optimizing data pipelines for performance and scalability.

Requirements

• Knowledge of programming languages (e.g. Java and Python)
• Hands-on experience with SQL database design
• Previous experience as a data engineer or in a similar role
• Technical expertise with data models, data mining, and segmentation techniques
• Great numerical and analytical skills
• Willingness to learn and work with new tools and technologies