We are seeking a Custom Software Engineer to design, code, and enhance components across systems and applications. This role involves leveraging modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs. The focus is on building AI-native data integration and data quality platforms using SAP BusinessObjects Data Services (BODS).

This position moves beyond traditional batch ETL into intelligent, self-optimizing data pipelines. These pipelines will reason about data structures, detect anomalies, recommend transformations, and accelerate data modernization without the need to train foundation models from scratch.

Key responsibilities include enterprise data integration, ETL engineering, data modeling, transformation, enrichment, quality, profiling, and governance. You will also build AI-native data engineering capabilities, develop robust testing and validation strategies, optimize for performance and scalability, and support operations and incident response.

Develop and operate BODS data integration jobs for diverse data types and systems. Implement robust batch and near real-time data pipelines supporting analytics, reporting, and data warehousing.

Design complex transformation logic and data enrichment processes using BODS features. Apply canonical data modeling to reduce complexity and duplication.

Implement data quality rules for validation, cleansing, and standardization. Build profiling pipelines to assess data completeness and accuracy. Support governance through lineage-aware jobs and audit trails.

Build data engineering agents for analyzing metadata, recommending transformations, and proposing data quality rules. Implement retrieval-grounded assistance for metadata catalogs and business rules.

Design automated validation strategies, including schema checks and reconciliation rules. Establish evaluation harnesses for AI behaviors and gate releases through quality thresholds.

Optimize ETL jobs for performance and scalability. Implement error handling, restartability, and recovery mechanisms for reliable operations.

Monitor job execution and data quality metrics. Perform root cause analysis for failures and document preventive actions.

Support modernization initiatives by integrating BODS pipelines with cloud platforms. Collaborate with architects and analytics teams to deliver end-to-end data solutions.

A minimum of 2 to 5 years of experience in software engineering is required, with a strong emphasis on SAP BusinessObjects Data Services (BODS) ETL development and operations.

Solid understanding of data integration patterns, transformation logic, and enterprise data quality practices is essential. Experience in designing reliable, scalable data pipelines with performance and governance in mind is crucial.

Primary skills include AI-native capabilities such as tool-augmented workflows, retrieval-grounded recommendations, evaluation loops, and safe automation boundaries.

Secondary, but strongly beneficial skills, include data warehousing and analytics fundamentals, metadata management, lineage concepts, data governance frameworks, and scripting or automation skills for pipeline orchestration.