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-solving skills with a focus on scalability, maintainability, and performance optimization.
• Strong communication skills and ability to collaborate with technical and business stakeholders.
• What about languages?
• English: Advanced (required for effective communication with global teams)
• How much experience must I have?
• 5+ years of experience in Data Engineering with demonstrated expertise in data modeling and ETL development.
• Vegetarian, vegan, gluten and sugar free options.

None flagged.