Our Journey
ShopBack began in 2014 as a late-night spark of inspiration between Henry and Joel — not just to build a Cashback platform, but to reimagine how brands and consumers connect. As former advertisers, they understood the limitations of traditional marketing, and saw an opportunity to deliver more value on both sides. That idea quickly turned into action, and the first prototype was built over a weekend with the other co-founders. Today, ShopBack serves over 50 million users across 13 markets, partners with 20,000+ merchants, and powers over half a million transactions daily. We're building The World’s Most Rewarding Way to Shop — and looking for bold, driven individuals to join us.
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 automated tools, including AI, to help our team screen applications, match candidates to roles, generate interview notes, and review assessments. These tools assist our recruiters and interviewers and they do not make final hiring decisions. 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].
