People deserve more from their money. More visibility, more control, and more freedom. Since 2015, the company has been on a mission to deliver just that. Our powerhouse of products — including spending, saving, investing, exchanging, and more — help our 65+ million customers get more from their money every day.
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Our Technology team is one of the best in the world, focused on building world-class financial features from the ground up that will be used by millions. Data platform engineers play a critical role in fostering a data-centric culture by providing the necessary infrastructure and tools for insight generation and decision-making across the company.
We are looking for a talented and passionate engineer who can manage our exponential growth in data and related complexity.
What You’ll Be Doing:
- Designing, building, and maintaining an efficient and reliable data platform.
- Partnering with cross-functional teams (Product, Engineering, Analytics) to translate abstract concepts into practical solutions.
- Establishing and enforcing data standards, maintaining comprehensive documentation.
- Training and supporting users, communicating platform updates and insights.
- Planning and executing organisation-wide platform changes, ensuring best practices for coding, testing, deployment, and maintenance.
- Leveraging data to guide all aspects of engineering work.
What You'll Need:
- A bachelor's or master's degree in computer science or a related field, or equivalent practical experience.
- Proficiency in Python, SQL, and Unix Shell scripting.
- Experience with agile software development best practices (TDD, refactoring, CI/CD).
- Demonstrated experience in custom ETL design and maintenance, with workflow orchestration using tools like Airflow.
- Extensive experience with distributed data processing and query engines (e.g., Trino, Spark, Snowflake).
- Experience building data platforms focusing on data quality, SQL performance tuning, and data warehousing principles.
- Experience building large-scale infrastructure applications and writing maintainable code in multiple languages.
Nice to Have:
- Expertise in cloud platforms (GCP, AWS), containerisation, and infrastructure-as-code (Docker, Kubernetes, Terraform).
- Understanding of modern data architecture and experience with data mesh principles.
- Familiarity with notebook-based data science workflows and monitoring tools.
The company is committed to creating a diverse and inclusive workplace and encourages applications from individuals with diverse backgrounds and experiences.
