Azure Databricks Engineer

About the role

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.

What you'll do

• Designing and developing end-to-end data pipelines using Azure Data Factory and Databricks, PySpark, SQL, Delta Lake
• Implementing data validation and quality frameworks to ensure data reliability. Writing efficient PySpark and SQL code for complex transformations, aggregations
• Managing secure access using Azure Key Vault, role-based permissions, and compliance best practices
• Working in an Agile/Scrum environment, delivering solutions aligned with business needs

What you need

• 4–12 years in data science & ai
• Databricks
• Azure
• SQL
• Python
• Spark
• CI/CD
• Any graduate

Good to have

• Scala
• Hive
• ETL
• Azure Data Factory

What you get