About Reward
Founded in 2001, Reward is an industry leader transforming the world of customer engagement and commerce media. Operating in 15 countries across Europe, Middle East and Asia, Reward’s cloud-based API platform integrates content, advertising, and commerce to deliver exceptional experiences for consumers resulting in increased customer engagement, retention, and overall satisfaction.
Reward’s Loyalty-tech platform is behind many award-winning bank loyalty programmes seen today from brands such as Visa, NatWest Group, Barclays, and First Abu Dhabi Bank to name a few. Reward also works with the world’s largest retailers such as McDonald’s, eBay, Deliveroo and Amazon.
Their leading commerce media platform fuses purchase insights with loyalty-tech, offering an unparalleled edge in digital advertising and performance marketing for retailers. Leveraging rich data and insights, the Reward platform provides a comprehensive view of consumer behaviour, empowering retailers to target marketing messages more effectively, resulting in independently verified sales uplift and long-term customer lifetime value.
Beyond bridging the gap between content and commerce, Reward is a purpose driven business. Their mission is to make everyday spending more rewarding. During the last 5 years, Reward has proudly given back more than $1billion in cashback rewards to consumers world-wide.
Most recently, Reward’s rapid growth was recognised in The Independent’s E2ETech100 list of fastest growing tech scale-ups in the UK. Reward, in conjunction with partners NatWest Group, was also awarded the Industry Achievement Award 2023 at the prestigious Card and Payments Awards.
Role Summary
We are seeking a highly skilled Data Engineer with strong experience managing large scale relational databases and building robust data solutions on AWS. The ideal candidate will have a proven track record of translating business requirements into technical specifications and delivering high quality, scalable data systems that support business intelligence, operations, and product growth.
You will work closely with cross functional teams including Data Science, Product, Engineering, and Operations to design, develop, and optimise data pipelines, storage solutions, and data models. This role is critical to ensuring our data ecosystem is secure, reliable, and built for scale.
Responsibilities
* Design, build, and maintain scalable ETL/ELT pipelines and data integration workflows.
* Manage, optimise, and monitor large-scale relational databases (e.g., PostgreSQL, MySQL, SQL Server).
* Architect and implement AWS based data solutions, including Redshift, S3, Glue, Lambda, or EMR.
* Translate business needs into technical specifications, ensuring data solutions align with stakeholder requirements.
* Develop and maintain data models, schemas, and documentation to support reporting and analytics.
* Ensure data quality, accuracy, and integrity through validation, testing, and monitoring.
* Implement and promote best practices in data security, governance, and performance optimisation.
* Support cross-functional teams with timely, reliable data access and insight delivery.
* Identify opportunities to automate processes and improve data systems for scalability and efficiency.
Requirements
* Proven experience as a Data Engineer or similar role.
* Strong hands on experience with large relational databases and SQL optimisation.
* Solid expertise in AWS data infrastructure and services (e.g., Redshift, Glue, Lambda, S3, Athena).
* Proficiency with ETL/ELT development and data integration tools.
* Experience building data models and supporting analytics workloads.
* Strong understanding of data warehousing concepts and best practices.
* Ability to translate business requirements into clear technical specifications.
* Experience with Python, Spark, or other data processing technologies (preferred).
* Familiarity with CI/CD tooling, infrastructure-as-code, or DevOps practices (a plus).
Personal Attributes
* Strong communication and stakeholder management skills.
* Analytical mindset with meticulous attention to detail.
* Proactive and able to operate in a fast-paced environment.
* Comfortable working both autonomously and collaboratively.
* Passionate about building scalable, high-performing data solutions.