Senior Data Engineer — Platform & Analytics

Revolut Ltd; España; On-site; EUR 60,000 - 90,000; Full time

Job summary

Revolut Ltd is seeking a Data Engineer to design, build, and maintain data platforms and automated ETL pipelines that power insights for teams across the company.

You will partner with Product, Engineering, and Data Science to translate abstract concepts into practical data solutions, while upholding data standards and documentation. A strong background in distributed data processing and cloud tooling is required.

Qualifications

• Bachelor'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 practices including TDD, refactoring, CI/CD, and XP.
• Demonstrated experience in designing and maintaining ETL pipelines, with Airflow or similar tooling.
• Expertise in distributed data processing and query engines (e.g., Trino, Spark, Snowflake, BigQuery).

Responsibilities

• Design, build, and maintain scalable data platforms and automated workflows.
• Collaborate with Product, Engineering, and Data Science to enhance the data platform.
• Establish and enforce data standards; maintain a company-wide data registry.
• Train and support users; communicate updates via dashboards and bots.
• Plan and execute platform changes with best practices for coding, testing, deployment, and maintenance.
• Leverage data to inform engineering decisions and drive insight-driven outcomes.

Skills

Python

SQL

Unix shell

Agile

TDD

CI/CD

XP

Education

Bachelor's degree in Computer Science or related field

Tools

Airflow

Trino

Spark

Snowflake

BigQuery

GCP

AWS

Docker

Kubernetes

Terraform

Job description

Revolut Ltd is seeking a Data Engineer to design, build, and maintain data platforms and automated ETL pipelines that power insights for teams across the company.

You will partner with Product, Engineering, and Data Science to translate abstract concepts into practical data solutions, while upholding data standards and documentation. A strong background in distributed data processing and cloud tooling is required.