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Choosing Capgemini means choosing a company where you will be empowered to shape yourcareer in the way you’d like, where you’ll be supported and inspired by a collaborativecommunity of colleagues around the world, and where you’ll be able to reimagine what’spossible. Join us and help the world’s leading organizations unlock the value of technology andbuild a more sustainable, more inclusive world.
Your Role:
1. Design and implement robust ETL/ELT pipelines on Databricks.
2. Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver high-quality solutions.
3. Optimize data workflows for performance, scalability.
4. Develop and maintain data lake and data warehouse architectures.
5. Ensure data quality, governance, and security standards are met.
6. Lead code reviews, mentor junior engineers, and contribute to best practices in data engineering.
7. Integrate Databricks with other enterprise systems and tools (e.g., Delta Lake, MLflow, Power BI, etc.).
8. Monitor and troubleshoot production data pipelines and jobs.
Your Profile:
9. Lead the design, development, and optimization of scalable data pipelines using Databricks.
10. Drive data modernization initiatives to support advanced analytics and machine learning.
11. Collaborate with cross-functional teams to understand data requirements and deliver robust solutions.
12. Implement best practices for data engineering, including performance tuning and cost optimization.
13. Ensure data quality, reliability, and consistency across all data platforms.
14. Leverage Databricks features such as Delta Lake, notebooks, and MLflow for end-to-end workflows.
15. Apply knowledge of data governance frameworks and tools, including Unity Catalog.
16. Maintain and enhance data security, access controls, and compliance standards.
17. Mentor junior engineers and contribute to the development of engineering standards.
18. Hold relevant Databricks certifications (e.g., Databricks Certified Data Engineer Professional).