Lead Data Engineer (Microsoft Fabric)

What is this position about? Conduct comprehensive gap analysis and data mapping across 80+ ERP systems to identify integration challenges, data inconsistencies, and transformation requirements. Design and develop standardized ETL pipelines and data transformation processes for migrating enterprise data into Microsoft Fabric. Build robust data quality frameworks and validation rules to ensure data readiness for AI and analytics workloads. Lead hands-on implementation of ETL standards and best practices, establishing repeatable patterns and automation scripts for multi-source integrations. Develop and optimize data models that support seamless transformation from fragmented ERP sources into a unified, AI-ready data architecture. Lead the pilot implementation phase, testing and refining standards against real ERP data before full-scale rollout. Mentor and guide team members on ETL development, data transformation techniques, and Fabric-specific engineering practices. Collaborate with stakeholders to document data lineage, transformation logic, and integration patterns for knowledge transfer and governance. Troubleshoot data inconsistencies and implement corrective measures to maintain data integrity throughout the pipeline. Advanced proficiency in SQL for complex data transformations, query optimization, and performance tuning. Strong Python expertise for automation scripting, data pipeline development, and ETL orchestration. Demonstrated hands-on experience in designing and implementing ETL solutions across complex, multi-source environments. Proven experience with enterprise ERP systems and large-scale data integration scenarios. Solid understanding of Azure ecosystem and hands-on experience with Microsoft Fabric for data engineering. Strong knowledge of data modeling principles and ability to design schemas that support AI and analytics use cases. Experience with data quality assessment, validation frameworks, and data profiling techniques. Excellent problem-solvin