About The Role

You will work with our Data team (mostly with Data Engineers and Analytics Engineers but also with Data Scientists and Data Analysts) together with Backend Engineers and SRE's to help us evolve and take our data platform to the next level.

This is a contractor position.

What Will You Do

• Work in a multi-cloud environment with GCP/AWS with cutting-edge technologies like Apache Airflow, Pub/sub, Snowflake, and Kubernetes among others, using Python as your main programming language.
• Build and maintain high-quality, reliable and robust data pipelines based on Python and deployed on Kubernetes and Airflow, that convert data streams into valuable information.
• Contribute to the development of new features and tools.
• Support our data architecture, based on real-time streaming and batch-processing solutions, supervising and maintaining the platform and the pipelines to guarantee its optimal performance. Help to implement strategies to optimize the performance and scalability of the data systems.
• Ensure that data architecture complies with security requirements.
• Contribute to maintaining the Continuous integration and deployment (CI/CD).

Who We Are Looking For

• Bachelor's Degree In Computer Science or similar and previous experience working in data or software engineering environments for at least 5 years.
• Solid background in DWH solutions, in particular in SQL databases (PostgreSQL, Snowflake, Redshift, etc.). Experience in noSQL databases (i.e MongoDB) is highly desirable.
• Coding proficiency in Python is a must.
• Team player, technology passionate and self-motivated individual.
• Strong written and verbal communication, and technical writing skills.
• Good writing/reading English level. Being fluent in English speaking is highly valuable.
• Experience working with bash scripting, Docker, Kubernetes and Linux environments is highly desirable.
• Experience with AWS/GCP stack or another cloud computing platform is highly valuable.

This is a contract position with a hybrid work model. The selected candidate will be expected to work onsite once a week during the initial onboarding period (typically the first 2–3 weeks). After this initial phase, the role will transition to being primarily remote, with occasional in-office presence only required during specific client visits or key meetings.