QUALIFICATONS: Strong written and verbal communication skills Experience with Microsoft Office including Excel and PowerPoint Practical application experience with data engineering tools and languages such as SQL, Python, Spark, and orchestration frameworks (e.g., Azure Data Factory or equivalent) Practical application experience with data architecture patterns and storage technologies (data lakes/lakehouse, warehouses, relational databases) and developing curated, reusable datasets Preferred experience building and operating ETL/ELT pipelines (batch and/or streaming), including data modeling, automated testing, monitoring, and incident triage Ability to communicate data architecture and data product concepts to a broad audience and partner effectively with reporting/analytics teams on downstream enablement Desire and ability to learn and leverage new software, tools, and processes in a self-learning environment Preferred experience managing and optimizing cloud/IT tooling costs (e.g., cost awareness, chargeback/showback concepts, and right-sizing) while meeting performance and reliability needs Preferred familiarity with AI/ML enablement patterns (e.g., feature-ready datasets, governed access, and integration with tools such as Azure ML). The Manager - Data Engineering is an IT leadership role focused on building and continuously improving a mature data platform and reusable data products that power enterprise reporting and self-service analytics, enable AI/ML solutions, and support operational decision-making.