Databricks Engineer

Capgemini is an AI-powered global business and technology transformation partner with nearly 60 years of heritage, employing over 420,000 team members in more than 50 countries. The company delivers end-to-end services and solutions across strategy, technology, design, engineering, and business operations. Capgemini Engineering provides R&D and engineering services across various industries, supporting innovative technologies such as autonomous cars and robotics.

• Bachelor’s degree in Computer Science, Engineering, Data Engineering, or a related discipline (or equivalent experience).
• Experience working as a Data Engineer or in a similar role.
• Strong experience with Databricks (or similar modern data platforms), SQL, and Python.
• Experience with data warehousing and lakehouse architectures.
• Data modelling and ETL/ELT experience.
• Understanding of Master Data Management (MDM) principles.
• Familiarity with APIs and data integration patterns, Git-based version control.
• Understanding of CI/CD, DevOps, and modern development practices.

• Design and develop data pipelines and data products within Databricks to support Augmented Delivery use cases.
• Build and maintain scalable data architectures, including data lakes, lakehouses, and data warehousing solutions.
• Develop and optimise SQL and Python-based data transformations.
• Support the development and implementation of Master Data Management (MDM) solutions for engineering asset standardisation and codification.
• Ensure data quality, consistency, and governance across platforms.
• Integrate data from multiple sources, enabling interoperability across engineering and digital systems.
• Collaborate with developers and digital engineering teams to enable data-driven use cases and automation.
• Work within modern development environments using DevOps practices, including CI/CD, version control, and testing.