Key Responsibilities • Data Pipeline Development: Design, develop, test, and deploy advanced ETL/ELT solutions to integrate data from various sources across the organization. • Data Modeling & Architecture: Create and maintain data models, schemas, and database architectures to support analytics and business intelligence requirements. • Cloud & Big Data Solutions: Leverage cloud platforms such as Azure Data Factory, Databricks, Synapse, and Cosmos to implement and optimize enterprise data solutions. • Data Quality & Governance: Uphold strict data quality standards, conduct needs assessments, and ensure data security and compliance—especially for federal health data. • Collaboration & Leadership: Work closely with cross-functional teams, provide mentorship to junior engineers, and serve as a technical SME throughout the software development lifecycle. • Continuous Improvement: Proactively identify opportunities to enhance business processes, technical capabilities, and delivery approaches. • Monitoring & Support: Oversee the health of data pipelines and systems, build monitoring tools and alerts, and address issues efficiently. Required Qualifications • Education: Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent professional experience. • 8+ years of experience in software and data engineering roles. • 6+ years of hands-on experience in data analysis, data modeling, ETL development (SSIS), and building data warehousing solutions. • 3+ years of experience with Azure Data Factory, Data Lake, and Databricks (Python/Spark). • 3+ years working with Star Schema and Snowflake Schema data models. • Solid experience working within the Azure cloud ecosystem. • Familiarity with federated data integration and data virtualization concepts. • Strong grasp of architecture principles, design patterns, and best practices. Preferred Qualifications • Experience with Snowflake. • Background in the healthcare industry.