AI Developer / AI-Assisted Data Engineer / Data Modernization Engineer

AI Developer / AI-Assisted Data Engineer / Data Modernization Engineer: The client is seeking an experienced AI Developer / AI-Assisted Data Engineer to support a large-scale enterprise data modernization initiative leveraging AI-assisted development and Microsoft Fabric technologies. The ideal candidate will help transform decentralized campus reporting assets and legacy Oracle-based CAP environments into scalable, governed, reusable enterprise data products within a modern Fabric lakehouse architecture. This role combines advanced data engineering, AI-assisted automation, metadata discovery, and enterprise modernization practices to accelerate migration from legacy reporting platforms into a scalable cloud-based ecosystem. The candidate will work collaboratively with architects, extraction teams, engineering teams, and campus IT stakeholders to establish repeatable modernization frameworks for systemwide deployment. The position requires deep expertise in Microsoft Fabric, PySpark, SQL, Python, ETL/ELT processes, AI-assisted development tools such as Copilot, and enterprise-scale data transformation initiatives. Strong analytical, automation, and collaboration skills are essential. Key Responsibilities • Develop automated scanning and inventory tools for Access, Excel, Power BI, SQL Server, and Oracle-based CAP environments. • Identify Oracle dependencies, reporting assets, data sources, and usage patterns across pilot campus environments. • Capture, structure, and analyze metadata to support AI-driven prioritization of data modernization initiatives. • Design and develop Bronze, Silver, and Gold data layers within Microsoft Fabric lakehouse environments. • Build scalable ETL/ELT pipelines, transformations, and reusable enterprise data products in Microsoft Fabric. • Utilize AI-assisted development tools to automate code generation, metadata analysis, modernization workflows, and migration activities. • Refactor legacy CAP assets into Fabric-based data solutions using AI-generated code and automation techniques. • Develop hybrid modernization strategies involving Access front-end and SQL backend integrations. • Build repeatable AI-assisted modernization workflows and migration playbooks. • Perform validation, reconciliation, and testing between Oracle REPL environments and Fabric outputs. • Ensure data quality, performance, completeness, and scalability across migrated solutions. • Document technical processes, scripts, methodologies, and onboarding materials. • Support knowledge transfer, training, and operational readiness activities. Additional Responsibilities • Collaborate with campus IT teams, data architects, and engineering stakeholders. • Assist with enterprise data governance and reusable data product initiatives. • Optimize large-scale data transformations for performance and scalability. • Support implementation of enterprise modernization frameworks across multiple institutions. • Recommend ingestion strategies and identify enterprise data gaps. • Contribute to long-term data modernization roadmaps and automation standards. Required Skills • 10+ years of experience in enterprise data engineering, analytics, or data architecture. • 5+ years of advanced SQL development experience. • 5+ years of advanced Python programming experience. • Strong ETL/ELT and enterprise data modeling expertise. • 3+ years of extensive experience with AI-assisted development tools such as Microsoft Copilot. • 3+ years of extensive PySpark development experience. • 3+ years of experience building and optimizing large-scale transformations in Microsoft Fabric lakehouse environments. • Strong experience with Microsoft Fabric and modern cloud-based data platforms. • Experience modernizing legacy enterprise reporting and analytics systems. • Knowledge of metadata discovery, governance, and enterprise data product development. • Strong analytical, automation, troubleshooting, and communication skills. • Experience with Power BI, SQL Server, Oracle, Access, and enterprise reporting systems preferred. Qualifications & Certifications • Bachelors degree in Computer Science, Data Engineering, Information Systems, or related field preferred. • Microsoft Fabric certification preferred. • Azure Data Engineering certifications preferred. • AI/ML or cloud platform certifications preferred. • Experience with enterprise-scale modernization and governance initiatives preferred. Expected Outcomes • Automated CAP inventory and metadata discovery processes. • AI-assisted prioritization and modernization analysis. • Delivery of scalable, reusable Fabric-based enterprise data products. • Successful migration of pilot campus reporting assets. • Establishment of repeatable modernization frameworks for enterprise-wide rollout.