Data Software Engineer
Revolut
Job Overview
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Job Description
About Revolut
People deserve more from their money. More visibility, more control, and more freedom. Since 2015, Revolut has been on a mission to deliver just that. Our powerhouse of products — including spending, saving, investing, exchanging, travelling, and more — help our 70+ million customers get more from their money every day.
As we continue our lightning-fast growth, 2 things are essential to our success: our people and our culture. In recognition of our outstanding employee experience, we've been certified as a Great Place to Work™. So far, we have 13,000+ people working around the world, from our offices and remotely, to help us achieve our mission. And we're looking for more brilliant people. People who love building great products, redefining success, and turning the complexity of a chaotic world into the simplicity of a beautiful solution.
About The Role
Our Technology team builds the systems and experiences that keep Revolut moving. From the infrastructure behind our innovative app to the features used by millions of people around the world, they bring sharp thinking, speed, and a focus on meaningful impact to everything they do.
We're looking for a Data Software 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.
Up to shape what's next in finance? Let's get in touch.
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)
Key skills/competency
- Data Engineering
- ETL
- Python
- SQL
- Airflow
- Distributed Systems
- Data Platforms
- Data Architecture
- CI/CD
- Cloud Computing (GCP/AWS)
How to Get Hired at Revolut
- Research Revolut's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Customize your resume to highlight Python, SQL, ETL, and distributed data processing experience relevant to a Data Software Engineer role at Revolut.
- Showcase data platform expertise: Prepare to discuss your experience designing, building, and maintaining efficient data platforms and automating workflows.
- Practice technical interviews: Be ready for coding challenges in Python/SQL and questions on data architecture, ETL, and cloud technologies (GCP/AWS).
- Emphasize collaboration and impact: Highlight how you partner with diverse teams and leverage data to drive meaningful insight and decision-making within an organization.
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