Data Engineer

Job Summary Data Engineer – Health • Lead a team in research and implementation of complex data engineering projects, including multiple data models, maps, and workflows. • Act as primary contact for the team, managing prioritization and execution of tasks. • Serve as Subject Matter Expert (SME), deeply understanding the data, its structure, and business context. • Design, develop, and deliver robust end-to-end data integration solutions following Data Engineering best practices and test-driven development. • Translate technical requirements into effective, scalable code solutions. • Develop new ETL/ELT pipelines between various source and target systems. • Perform unit testing to ensure data accuracy and system reliability. • Develop and optimize data models using industry-standard techniques (e.g., slowly changing dimensions, star schemas, data vault). • Apply data warehousing concepts, including Kimball and Inmon methodologies, DDS, ODS, and data flow from source systems to BI tools. • Utilize advanced SQL skills, including DDL/DML operations, normalization, relational data modeling, ACID transactions, and performance/security best practices. • Demonstrate senior-level expertise in JavaScript and experience with NoSQL/non-relational databases. • Exhibit strong experience with Snowflake and Azure Cloud technologies. • Act independently as a self-starter, proactively identifying and solving problems. • Healthcare industry experience required. • Strong communication skills (rated 9/10). • Remote work for candidates in EST or CST time zones.