Senior Data Engineer based in Ann Arbor, Michigan, United States, responsible for designing, building, and scaling enterprise-grade data pipelines on cloud-native platforms (Azure and Databricks). You will partner with Data Architects, Platform Engineers, Cloud Engineers, Product Owners, and cross-functional stakeholders to translate strategy and architecture into production-grade, high-quality solutions. Responsibilities include designing and implementing scalable ingestion, transformation, and data product frameworks for structured, semi-structured, and unstructured data at enterprise scale; automating ingestion, processing, validation, and monitoring to ensure reliability and observability; driving future-state data architecture and cloud migration patterns to ensure secure, maintainable systems aligned with modernization goals; optimizing workflows for performance and cost using Delta Lake, partitioning, caching, and compute scaling; defining data access controls and RBAC with security and governance teams; providing technical leadership, mentoring engineers, and promoting best practices for CI/CD, testing, automation, and observability; partnering with AI/ML, analytics, and business teams to enable real-time and batch data activation use cases that improve decision-making and business outcomes; ensuring compliance with data governance, privacy, and security standards. Qualifications include 8+ years of experience in data engineering, strong expertise with Databricks, Spark, Delta Lake, Azure services, data integration and modeling; experience building large-scale ETL/E

Senior Data Engineer based in Ann Arbor, Michigan, United States, responsible for designing, building, and scaling enterprise-grade data pipelines on cloud-native platforms (Azure and Databricks). You will partner with Data Architects, Platform Engineers, Cloud Engineers, Product Owners, and cross-functional stakeholders to translate strategy and architecture into production-grade, high-quality solutions. Responsibilities include designing and implementing scalable ingestion, transformation, and data product frameworks for structured, semi-structured, and unstructured data at enterprise scale; automating ingestion, processing, validation, and monitoring to ensure reliability and observability; driving future-state data architecture and cloud migration patterns to ensure secure, maintainable systems aligned with modernization goals; optimizing workflows for performance and cost using Delta Lake, partitioning, caching, and compute scaling; defining data access controls and RBAC with security and governance teams; providing technical leadership, mentoring engineers, and promoting best practices for CI/CD, testing, automation, and observability; partnering with AI/ML, analytics, and business teams to enable real-time and batch data activation use cases that improve decision-making and business outcomes; ensuring compliance with data governance, privacy, and security standards. Qualifications include 8+ years of experience in data engineering, strong expertise with Databricks, Spark, Delta Lake, Azure services, data integration and modeling; experience building large-scale ETL/E