▷ [Immediate Start] Data Engineering Expert – Financial Data Pipeline Development

1 week ago


Pune, 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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