Data Engineer

Capgemini is an AI-powered global business and technology transformation partner with nearly 60 years of heritage, employing over 420,000 team members in more than 50 countries. The company delivers end-to-end services and solutions with deep industry expertise and a strong partner ecosystem, reporting 2025 global revenues of €22.5 billion.

• Experience as a Data Engineer with strong practical skills in data processing.
• Proficiency in Python for data manipulation, automation and integration.
• Experience working with cloud environments (AWS, Azure or GCP).
• Experience working with large datasets and distributed data systems.
• Hands-on experience with relational and/or NoSQL databases.
• Clear and effective communication skills in English.

• Design, build and maintain ETL/ELT data pipelines in cloud and distributed environments.
• Process, clean and transform large datasets across various platforms.
• Integrate data from multiple systems including databases, APIs and streaming sources.
• Ensure data quality, consistency and performance across workflows and environments.
• Work closely with Data Architects, analysts and product teams to implement data solutions.
• Participate in code reviews and follow engineering best practices.
• Support data workflow automation and CI/CD processes using orchestration tools (e.g. Airflow, Prefect).
• Use modern data platforms such as Databricks in production or development environments.

Capgemini is committed to diversity and inclusion, ensuring fairness in all employment practices. Individuals are evaluated based on qualifications and performance, not personal characteristics.