Data Engineering Expert – Financial Data Pipeline Development

9 hours ago

bangalore, India Elongo Global Solutions Full time

🌍 About the Role We’re looking for a Data Engineering Expert to design and build a financial data pipeline that connects SAP BW and SAP BFC to our Azure Data Platform. This role is crucial in enabling seamless integration and real-time flow of financial data, which will later power AI-driven predictive models for company KPI forecasting. If you have hands-on experience in Azure Functions, Kafka, MS Fabric, and deep knowledge of SAP financial systems, this is your chance to shape a high-impact project that merges finance, data engineering, and AI innovation. 🎯 Your Mission You’ll lead the development of an end-to-end financial data pipeline — from data ingestion to analytics readiness — ensuring scalability, accuracy, and security across all stages. 🔧 Key Responsibilities Design & Build Pipelines: Develop robust and secure data pipelines between SAP BW, SAP BFC, and Azure Data Platform. Data Integration: Streamline data ingestion from SAP systems to Azure using Azure Functions, Kafka, and MS Fabric. Optimize Performance: Ensure efficient, real-time data processing for financial reporting and analytics. Enable AI Insights: Structure and prepare data for consumption by AI models to predict company KPIs. Documentation & Support: Deliver detailed documentation, handover materials, and team training for future maintenance. 🧩 Required Skills & Expertise Proven experience with Azure Data Engineering and pipeline development. Strong hands-on knowledge of SAP BW and SAP BFC (financial consolidation and reporting). Proficiency in Azure Functions, Apache Kafka, and MS Fabric. Solid understanding of financial data structures and ETL processes. Working knowledge of Python for data transformation and automation. Strong understanding of data security, integrity, and governance principles. 💡 Nice to Have Experience integrating financial ERP data into cloud-based analytics platforms. Familiarity with AI/ML model data preparation or predictive analytics. Exposure to real-time data streaming and event-driven architectures. 

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