Innovate and build AI-native data integration and quality platforms. This role leverages SAP BusinessObjects Data Services (BODS) to combine deep ETL, data management, and metadata expertise with agentic AI patterns. Focus on creating intelligent, self-optimizing data pipelines that can understand data structures, identify anomalies, suggest transformations, and accelerate data modernization.

Design, develop, and operate BODS data integration jobs for diverse systems. Implement robust batch and near real-time data pipelines supporting analytics and data warehousing. Build reusable data flows and implement complex transformation logic using BODS features. Implement data quality rules, profiling, and governance. Develop AI-native data engineering agents for transformation logic recommendation and data quality rule proposal. Design automated validation strategies and evaluation harnesses for AI behaviors. Optimize ETL jobs for performance and scalability, implementing error handling and recovery mechanisms. Monitor pipelines, perform root cause analysis, and utilize AI-augmented diagnostics for issue resolution. Support modernization initiatives by integrating BODS pipelines with cloud platforms and analytics ecosystems.

A minimum of 2-5 years of experience is required. Essential skills include strong, hands-on expertise in SAP BusinessObjects Data Services (BODS) ETL development and operations. A solid understanding of data integration patterns, transformation logic, and enterprise data quality practices is crucial. Experience designing reliable, scalable data pipelines with performance and governance in mind is expected. Proficiency in AI-native capabilities such as tool-augmented workflows, retrieval-grounded recommendations, evaluation loops, and safe automation boundaries is necessary. A 15-year full-time education is mandatory.