Azure Data Engineer

Capgemini is a global leader partnering with companies to transform and manage their business by harnessing the power of technology. The Insights & Data team is a dynamic group of over 400 professionals delivering cutting-edge data solutions specializing in Cloud & Big Data engineering across AWS, Azure, and GCP.

• Strong experience in data engineering, including working with Azure.
• Strong Python skills for data processing and automation.
• Hands-on experience with Databricks, Snowflake, or Microsoft Fabric.
• Strong communication skills and very good English language skills.

Nice to have:

• Strong SQL skills and experience with database optimization.
• Knowledge of DevOps practices, CI/CD pipelines, and Infrastructure as Code tools (Terraform, Bicep).
• Familiarity with Azure services: Data Lake, Event Hub, Data Factory, Synapse Analytics, Azure Functions.
• Exposure to containerization (Docker, Kubernetes) and cloud security best practices.
• Experience in real-time data processing and streaming technologies like Kafka or Spark Streaming.
• Hands-on experience with PySpark.
• Certifications such as DP-900, DP-203, AZ-204, or AZ-400.

• Design and implement Azure-based data solutions for large-scale and unstructured datasets.
• Develop and optimize data pipelines using Azure Data Factory, Databricks, or Snowflake.
• Collaborate with solution architects to define and implement best practices in data engineering.
• Ensure data quality, scalability, and security across all Azure-based solutions.