Custom Software Engineer

Custom Software Engineer

Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.

Must have skills: SAP BusinessObjects Data Services

Minimum 3 year(s) of experience is required. Educational Qualification: 15 years full time education.

Build AI native data integration and data quality platforms using SAP BusinessObjects Data Services (BODS) by combining deep ETL, data management, and metadata expertise with agentic AI patterns (LLMs + tools + retrieval + evaluation). This role focuses on moving beyond traditional batch ETL into intelligent, self optimizing data pipelines that can reason about data structures, detect anomalies, recommend transformations, and accelerate data modernization—without training foundation models from scratch.

Core Responsibilities:

• Enterprise Data Integration & ETL Engineering
• Data Modeling, Transformation & Enrichment
• Data Quality, Profiling & Governance
• AI Native Data Engineering (Agentic ETL Layer)
• Testing, Validation & Evaluation Loops
• Performance, Scalability & Reliability
• Operations, Monitoring & Incident Response
• Modernization & Platform Evolution

Primary Skills (AI Native Must Have): Strong hands on expertise in SAP BusinessObjects Data Services (BODS) ETL development and operations. Solid understanding of data integration patterns, transformation logic, and enterprise data quality practices. Experience designing reliable, scalable data pipelines with performance and governance in mind. AI native capability: tool augmented workflows, retrieval grounded recommendations, evaluation loops, and safe automation boundaries.

Secondary / Strongly Beneficial Skills: Data warehousing and analytics fundamentals (facts, dimensions, hierarchies, reconciliation). Metadata management, lineage concepts, and data governance frameworks. Experience integrating ETL platforms with cloud data ecosystems and modern analytics tools. Scripting or automation skills to support pipeline orchestration and operational tooling.

Value Delivered: Faster data pipeline development through intelligent ETL scaffolding and grounded recommendations. Higher data trust via automated quality rules, anomaly detection, and evaluation loops. Scalable, modern data integration foundations that support analytics, AI, and enterprise decision making.

Additional Information: A 15 years full time education is required. 15 years full time education