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- Tasks: Design and maintain data platforms that drive insights for everyone at Revolut.
- Company: Join a leading fintech company revolutionising the finance industry.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and cutting-edge technology.
- Why this job: Shape the future of finance with innovative data solutions and impactful projects.
- Qualifications: Degree in computer science or equivalent experience; skills in Python, SQL, and data processing.
The predicted salary is between 60000 - 80000 £ per year.
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 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).
Software Engineer (Data) employer: Alfa AI
Contact Detail:
Alfa AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer (Data)
✨Tip Number 1
Network like a pro! Reach out to current employees at Revolut on LinkedIn or through mutual connections. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or GitHub with projects that highlight your data engineering prowess, make sure to share it during interviews. It’s a great way to demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python, SQL, and ETL processes. Practise coding challenges and be ready to discuss your past projects in detail. We want to see how you think and solve problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Revolut.
We think you need these skills to ace Software Engineer (Data)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Data Engineer. Highlight your experience with Python, SQL, and any relevant projects that showcase your skills in building data platforms. We want to see how you can bring your unique flair to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background aligns with our mission at Revolut. Let us know how you can contribute to our data-centric culture.
Showcase Your Projects: If you've worked on any cool projects, especially those involving ETL processes or cloud infrastructure, make sure to mention them! We love seeing practical examples of your work that demonstrate your problem-solving skills and technical expertise.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our awesome team at StudySmarter!
How to prepare for a job interview at Alfa AI
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, SQL, and Unix Shell scripting. Brush up on your knowledge of distributed data processing tools like Spark and BigQuery, as well as cloud platforms like GCP or AWS. Being able to discuss these confidently will show that you're ready to hit the ground running.
✨Showcase Your Collaboration Skills
Since the role involves partnering with cross-functional teams, be prepared to share examples of how you've successfully collaborated in the past. Think about specific projects where you worked with product managers or data scientists, and highlight how your contributions made a difference.
✨Demonstrate Problem-Solving Abilities
Prepare to discuss how you've tackled complex data challenges in previous roles. Use the STAR method (Situation, Task, Action, Result) to structure your answers, focusing on how you designed and implemented efficient data solutions or automated workflows.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company’s data culture and future projects. Inquire about their current data architecture or how they implement best practices for coding and deployment. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.