• 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.

• 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.

• Build, maintain and optimize data pipelines • Propose improvements and lead data modeling in partnership with business stakeholders • Work with a multidisciplinary team to drive business growth

• Support various stages of traffic and transportation analysis and design for data center developments across the United States. • Collect, review, and analyze traffic and transportation data to evaluate roadway operations, site access, and traffic impacts. • Prepare technical reports, exhibits, and recommendations that support project planning, permitting, and design efforts. • Collaborate with multidisciplinary teams and assist with client and agency coordination throughout project delivery. • Apply traffic engineering principles, company standards, and industry best practices while contributing to multiple projects and meeting project deadlines.