We are looking for a Data & Cloud Engineering Intern to join our team engaged in digital transformation, focusing on advanced projects in cloud infrastructure and data pipelines. As a Data & Cloud intern, you will have the opportunity to contribute to innovative projects while developing your skills in modern cloud environments, automation, and data processing for user profiling.

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Your Role

Cloud Responsibilities:
• Participate in the deployment and management of multiple cloud-based applications.
• Support the automation and optimization of infrastructure environments.

Data Responsibilities:
• Design and implement data pipelines for advanced user profiling.
• Apply AI and machine learning techniques to enhance data analysis and user understanding.

Your Team

Within our multidisciplinary team, you will work in a dynamic and collaborative environment where innovation is encouraged. This internship is a unique opportunity to deepen your knowledge in Data and Cloud Engineering while contributing meaningfully to projects that have a direct impact on our products and services.

Your Qualifications

• Good understanding of cloud computing concepts and infrastructure management.
• Familiarity with automation and deployment tools.
• Experience with data pipeline management tools such as Apache Spark, Kafka, Apache Airflow or Dagster.
• Knowledge of AI and machine learning applied to data-driven user profiling.

Benefits

This internship offers a hands-on, immersive experience where you’ll work directly on impactful, real-world projects involving Data Engineering and Cloud Infrastructure. You’ll benefit from close mentorship, exposure to modern DevOps and AI technologies, and the opportunity to build strong technical foundations for your professional future.

Joining us means becoming part of a team that values innovation, collaboration, and continuous learning.

Recruitment Process

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Our recruitment process takes place over the course of a single day and includes:

1. Technical Test
2. Technical Interview
3. Last Interview

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