Capgemini (FS) Optimus a data pipeline optimization service

In modern data engineering projects whether greenfield or re engineering building and testing ETL pipelines is a time consuming and skill intensive process. Manual coding from source to target mapping documents, often prepared by data analysts, slows down development and introduces quality risks, especially when junior developers are involved. Our services help to leverages Agentic AI and GenAI LLMs to automate the generation of ETL code (Spark/SQL) and corresponding test cases directly from mapping specifications. This dramatically reduces development effort, enhances code quality, and supports test-driven development practices. By transforming mapping documents into production ready ETL pipelines, the solution empowers data engineers to focus on optimization and delivery rather than manual coding and debugging. It bridges skill gaps, improves productivity, and ensures consistent, high quality output across teams.