Data Engineer (Databricks + PySpark)

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Your Role

• Design and implement robust, scalable data pipelines (e.g., ADF Pipelines, Databricks).
• Develop maintainable ETL pipelines using PySpark following coding guidelines.
• Perform data model development and versioning.
• Work with Azure cloud infrastructure: Data Factory, Data Lake, Databricks.
• Develop and monitor schema and data migrations.
• Optimize ETL performance.
• Transform SQL code into Databricks workflows written in Python.
  
  

Your Profile

• Programming: Python, PySpark, PowerShell (optional), pytest (optional).
• Databases: SQL, MS SQL Server, T-SQL, data modelling techniques.
• Azure Stack: Azure Data Factory, Azure Data Lake, Azure Databricks, Azure Cosmos DB.
• Practices & Tools: Clean code, DevOps, Testing, CI/CD (Azure DevOps, Git).
• Operating Systems: Windows, Azure.
• Methods: Scrum, Agile.
  
  

Nice to have skills:

• PowerBI.
• Additional programming languages.
• Object-oriented programming.
  
  

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.

Make it real | www.capgemini.com