Data Engineering Intern

Our Journey

The ShopBack Group is Asia-Pacific’s leading shopping, rewards, and payments platform, serving over 60 million shoppers across 13 markets. In 2025, the Group continued its global growth with its expansion into North America. Driven by the vision to make every day more rewarding, ShopBack is dedicated to saving members money and time, and delivering delight every day. The platform also enables merchants and brands to engage with their members in a cost-effective manner. Founded in 2014, ShopBack now powers over US$5.5 billion in annual sales for over 20,000 online and in-store partners, and has rewarded shoppers with more than US$800 million (over S$1 billion) in Cashback to date. Through its innovative offerings, ShopBack continues to create value for both members and merchants. Notably, its payment solution, ShopBack Pay, offers members a convenient and rewarding payment option at checkout.

About The Role

At ShopBack, our engineering teams build scalable platforms and utilize leading technologies to build a world-class product. You will join a diverse and talented team of aspiring engineers with great ambition to impact the eCommerce landscape. We are seeking team members who strive to solve hard problems, take pride in delivering world-class products, and are strong team players. You will get an opportunity to work on building scalable data systems that help drive the organization’s data-driven decision-making and play a direct impact on growth.

Our Data Platform team builds and maintains the foundation that powers ShopBack’s analytics and decision-making.

We design and operate data pipelines across AWS S3, Apache Iceberg, and Trino, orchestrated through Airflow and modeled via dbt-on-Spark. You’ll work alongside experienced data engineers who value clean data, efficient systems, and thoughtful design, not just working code.

Your Adventure Ahead

• Build and maintain data models and pipelines using Spark and Apache Airflow
• Learn to design and optimize HUDI and Iceberg tables for performance and reliability
• Write and validate SQL transformations consumed in Trino and Metabase
• Collaborate with senior engineers to improve data quality and observability
• Use AI tools (e.g., ChatGPT, Cursor, Claude Code) to assist coding and documentation, and learn how to verify their output
• Document learnings and share improvements through Confluence and Slack

What You Will Learn

• How modern data lakehouses (Spark + Iceberg + Trino) work in production
• Building reliable, testable dbt models on top of large datasets
• End-to-end flow: ingestion → transformation → analytics
• Practical debugging, observability, and version control in a real system
• How to collaborate effectively in a hybrid engineering team

Essentials To Succeed

• Strong interest in data engineering or data systems
• Familiarity with Python and SQL (school projects or self-taught is fine)
• Curiosity about data pipelines, storage formats, and data quality
• Comfort experimenting with AI coding assistants responsibly
• Clear communication, asks questions early, shares progress regularly
• Bonus: exposure to AWS, dbt, Spark, or Trino

ShopBackers' DNA

• Grit - We tackle all challenges head-on, working together to solve problems and achieve success.
• Hunger - We value hard work, and having relentless drive.
• Speed - We move fast and have a bias for action, all to deliver maximum impact.
• Impact - We focus on results, always aiming for the best possible outcomes and timelines.
• Growth - We embrace a growth mindset, constantly striving to learn, improve, and excel in our roles.

Exclusively for ShopBackers

• Career progression paths and opportunities to take on greater challenges that help you realise your ambitions.
• Be part of a winning team on a journey to global scale.
• Competitive compensation based on your performance.
• Candid, open, and collaborative culture where feedback is valued, for everyone to grow and improve every day.

ShopBack is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sexual orientation, national origin, age, disability, genetic information, veteran status, or any other protected status under applicable laws. Join our team and help us make a difference!

We are committed to protecting your data and ensuring fairness in our recruitment process. We may use artificial intelligence (AI) tools to help our team review applications, analyse resumes, match candidates to roles, generate interview notes, and assess responses. These tools assist our recruiters and interviewers and they do not make final hiring decisions. Final hiring decisions are ultimately made by humans. If an assessment is part of your process, we may (with your consent) capture screen activity and/or webcam images during the test to help verify test integrity. We do not use AI to infer your emotions or sensitive traits. We process personal data lawfully, securely, and transparently in line with applicable data-protection laws and our commitment to fair employment. You can ask questions or exercise your rights including to request human review or to challenge an outcome by contacting [email protected] .