Spearhead the development of AI-native data integration and quality platforms. This role involves leveraging SAP BusinessObjects Data Services (BODS) and cutting-edge AI patterns to create intelligent, self-optimizing data pipelines. Move beyond traditional ETL to build solutions that can understand data structures, identify anomalies, and accelerate data modernization without the need for foundational model training.

Design, develop, and operate BODS data integration jobs for diverse systems, implementing robust batch and near real-time pipelines. Build reusable data flows and transforms, and design complex transformation logic with BODS features. Implement data quality rules, profiling, and validation pipelines, while supporting governance requirements. Develop AI-driven data engineering agents for metadata analysis, rule proposal, and automated ETL scaffolding. Implement automated validation strategies and establish evaluation harnesses for AI behaviors. Optimize ETL jobs for performance and scalability, and implement error handling for reliable operations. Monitor job execution, perform root cause analysis, and utilize AI diagnostics for issue resolution. Support modernization initiatives by integrating BODS pipelines with cloud platforms and collaborate with cross-functional teams.

Requires a minimum of 3 years of experience in SAP BusinessObjects Data Services (BODS) ETL development and operations. A strong understanding of data integration patterns, transformation logic, and enterprise data quality practices is essential. Experience in designing reliable, scalable data pipelines with a focus on performance and governance is crucial. 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 a mandatory requirement for this position.