Data Warehouse Engineer

At Capgemini’s Insights & Data practice, we help organizations unlock the value of data, analytics, and modern technologies to make better business decisions. We deliver projects for global clients across various industries, combining deep technical expertise with a strong understanding of business processes. This role is part of a project delivered for a leading insurance client focusing on maintaining and enhancing mission-critical Data Warehouse solutions operating within a complex enterprise environment. Capgemini is a global organization with over 410,000 team members in more than 50 countries and reported 2025 revenues of €22.5 billion.

• Hands-on experience in Data Warehousing and data integration environments.
• Experience supporting, maintaining, or developing complex data platforms.
• Comfortable working in structured, process-driven environments with established quality standards.
• Ability to understand and navigate large-scale, highly integrated systems.
• Strong team player with a collaborative mindset and willingness to share knowledge.
• High attention to detail, accountability, and commitment to delivering quality solutions.
• Ability to work in an environment that requires a gradual learning curve and deep domain understanding.
• Practical experience with:
  • Oracle Database (RDBMS)
  • PL/SQL
  • Oracle Data Integrator (ODI)
  • Oracle GoldenGate
  • Java
  • Linux/Bash
  • Git
  • CI/CD tools and practices
  • Data Modelling and Data Warehousing concepts

Nice to have:

• Experience within the Insurance or Financial Services sector.
• Basic knowledge of German.
• Experience supporting legacy system modernization or transformation initiatives.
• Experience working in small, highly specialized teams.
• Knowledge of data quality management, data lineage, and governance practices.

• Maintain and enhance existing Data Warehouse solutions operating within a legacy environment.
• Support, monitor, and troubleshoot ETL/ELT processes and data integration pipelines.
• Analyze dependencies between systems and ensure consistency of data flows across the landscape.
• Implement changes in line with established standards, governance principles, and operational processes.
• Collaborate closely with team members to ensure platform stability and business continuity.
• Create and maintain technical documentation, specifications, and data lineage artifacts.
• Ensure high data quality, process reliability, and production system stability.
• Assess the impact of proposed changes on existing solutions and business processes.