Develop innovative custom software solutions designed to enhance and integrate system components. This role emphasizes the use of modern frameworks and agile methodologies to deliver scalable, high-performance applications tailored to specific business requirements.

The position involves building AI-native data integration and data quality platforms. You will leverage expertise in ETL, data management, and metadata combined with agentic AI patterns. The focus is on creating intelligent, self-optimizing data pipelines that can analyze data structures, identify anomalies, suggest transformations, and accelerate data modernization without requiring the training of foundational AI models.

Design and execute enterprise data integration and ETL processes using SAP BusinessObjects Data Services (BODS), ensuring compatibility with both SAP and non-SAP systems.

Implement robust data pipelines for analytics, data warehousing, and downstream applications, supporting both batch and near real-time data flows.

Develop complex data transformations and enrichment logic, applying canonical data modeling practices for efficiency and standardization.

Build data quality, profiling, and governance solutions, including implementing validation rules and supporting lineage tracking.

Create AI-powered data engineering agents capable of analyzing metadata, recommending transformations, proposing data quality rules, and auto-generating ETL code.

Establish automated testing and validation strategies, including schema checks, reconciliation rules, and regression comparisons.

Optimize ETL jobs for performance and scalability, ensuring reliable operations through robust error handling and recovery mechanisms.

Monitor pipeline execution, analyze root causes of failures, and utilize AI for diagnostics and incident response.

Support modernization initiatives by integrating BODS pipelines with cloud data platforms and collaborating on evolving data architectures.

A minimum of 2-5 years of professional experience is required, with a minimum of 3 years in SAP BusinessObjects Data Services (BODS) ETL development and operations.

Essential skills include strong hands-on expertise in BODS, a solid understanding of data integration patterns, transformation logic, and enterprise data quality practices.

Demonstrated experience in designing scalable data pipelines with a focus on performance and governance is necessary.

Familiarity with AI-native capabilities such as tool-augmented workflows, retrieval-grounded recommendations, evaluation loops, and safe automation boundaries is crucial.

Beneficial skills include data warehousing fundamentals, metadata management, data lineage concepts, and experience with cloud data ecosystems and modern analytics tools. Scripting or automation skills for pipeline orchestration and operational tooling are also advantageous.