Job description

Company culture :

Capgemini is characterized by a predominantly collaborative culture, placing people, trust and teamwork at the core of its practices. A close management approach fosters guidance, empowerment and skills development within a supportive environment. This culture is reinforced by a strong organizational dimension, ensuring process rigor, reliability and operational efficiency. It is complemented by a competitive component focused on performance and customer satisfaction, while a more moderate innovation dimension supports the continuous evolution of services and expertise.

Within our project teams, you will contribute to the development of innovative digital solutions for large clients in the banking, insurance, energy, and industry sectors. You will join a multidisciplinary team, organized in an Agile mode, working on projects with significant business impact.

As a Databricks Data Engineer, you will be involved in various missions such as:

• Design and develop efficient and scalable data pipelines on Databricks.
• Utilize advanced Apache Spark functionalities via PySpark for big data processing.
• Participate in data modeling, performance optimization, and the implementation of best practices.
• Collaborate with Data Science, BI, and business teams to meet business needs.
• Integrate solutions into CI/CD environments, using tools like Git, Azure DevOps, Terraform.
• Provide technical guidance to junior profiles and contribute to technological watch.
  

• Graduate degree (Bac+5 or equivalent) in computer science or related field.
• Proven experience (≥ 5 years) in a similar role.
• Proven experience in data engineering with Databricks.
• Proficiency in PySpark, SQL, and cloud environments (Azure, AWS, or GCP).
• Knowledge of orchestration tools (Airflow, Azure Data Factory, etc.).
• Analytical skills, autonomy, rigor, and ability to work in a team. A Databricks or cloud certification is a plus.