Software Engineer (Data)

Software Engineer (Data)

Revolut

Multiple Locations

About the role

We're looking for a Data Engineer to provide the infrastructure and tools that power insight generation and decision-making for everyone at Revolut, from entry-level analysts to C-level executives. You'll use your exceptional building and collaboration skills to uphold our data-centric culture.

What you’ll be doing

• Designing, building, and maintaining efficient and reliable data platforms, streamlining end-to-end processes and automating workflows
• Partnering with cross-functional teams (Product, Engineering, Data Science) to build and enhance a seamless data platform, translating abstract concepts into practical solutions
• Establishing and enforcing data standards, maintaining comprehensive documentation, and managing a company-wide data registry
• Training and supporting users, and communicating platform updates and insights through various channels (dashboards, bots, etc.)
• Planning and executing organisation-wide platform changes, ensuring consistent best practices for coding, testing, deployment, and maintenance
• Leveraging data to guide all aspects of engineering work, ensuring insight-driven outcomes

What you'll need

• A bachelor's or master's degree in computer science or related field, or equivalent practical experience
• Proficiency in Python, SQL, and Unix Shell scripting
• Experience implementing agile software development best practices, including TDD, refactoring, CI/CD, and XP
• Demonstrated experience in custom ETL design, implementation, and maintenance, along with workflow orchestration using tools like Airflow
• Expertise in distributed data processing and query engines (e.g., Trino, Spark, Snowflake, BigQuery)

Nice to have

• Experience building large-scale infrastructure applications and writing maintainable code in multiple programming languages
• Expertise in cloud (GCP, AWS), containerisation, and infrastructure as code (Docker, Kubernetes, Terraform)
• An understanding of modern data architecture with experience implementing data mesh principles
• Familiarity with notebook-based data science workflows and proficiency in using monitoring and logging tools (NewRelic, Grafana, Prometheus, ELK)