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. [+]
Job :
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 high business impact.
As a Big Data Engineer, you will be involved in various tasks such as:
• Design, develop, and maintain robust data pipelines using Scala, PySpark, or Hadoop.
• Optimize distributed processing and ensure the performance of jobs on Big Data clusters.
• Integrate and transform data from various sources using Hive and other tools from the Hadoop stack.
• Collaborate with Data Science and BI teams to provide reliable and scalable datasets.
• Ensure data quality, security, and governance in a Big Data environment.
Required profile :
Degree in Computer Science, Data Engineering, or a similar field.
Proven experience (5+ years) in Big Data development with Scala, PySpark, Hadoop, and Hive.
Good command of distributed processing concepts, parallelism, and performance optimization.
Knowledge of Big Data ecosystems (HDFS, YARN, Spark SQL) and data engineering best practices.
Ability to work in a team, analytical skills, and ability to solve complex problems.