Senior Data Engineer (Databricks)

About the role

Capgemini Engineering is seeking a Senior Data Engineer with strong Databricks expertise to join global data and analytics projects, working with distributed teams and modernizing data platforms.

Key responsibilities

• Design and develop data solutions based on Databricks.
• Build and maintain scalable data pipelines.
• Implement DataOps practices and automation.
• Define data governance and quality standards.
• Collaborate with business and technology teams to deliver analytical solutions.

Required profile

• 7+ years of experience in Data Engineering.
• Solid experience with Databricks and Apache Spark (PySpark/Spark SQL).
• Experience with dbt, Airflow or Databricks Workflows.
• Proficiency in SQL and Python.
• Knowledge of Lakehouse architecture and data modeling.
• Experience working on AWS, Azure or Google Cloud.
• Intermediate/advanced English.

Required skills

• Databricks
• Apache Spark
• PySpark
• Spark SQL
• dbt
• Airflow
• Databricks Workflows
• SQL
• Python
• Lakehouse architecture
• Data modeling
• AWS
• Azure
• Google Cloud
• Kafka (desired)
• Fivetran (desired)
• Pub/Sub (desired)
• Unity Catalog (desired)
• Immuta (desired)
• Power BI (desired)
• Databricks Data Engineer Professional certification (desired)
• AI/ML or GenAI knowledge (desired)

What we offer

• Virtual expense reimbursement.
• OSDE health plan.
• Benefits at Megatlon and Fiter.
• 70% discount on language courses (English, French, Portuguese).
• Courses and certifications via Udemy and NextLI-LB21.