Senior Data Engineer

A healthcare technology organization is seeking a Senior Data Engineer to build and optimize enterprise data solutions using Snowflake and Azure., The position combines hands-on data warehouse engineering, SQL development, scalable data pipelines, data modeling, and production reliability. The engineer will work with complex datasets, including healthcare-related information, while helping analytical and operational teams access reliable, well-governed data., * Design, build, and optimize cloud data warehouse structures in Snowflake.

• Develop and maintain Azure-based data ingestion and transformation pipelines.
• Implement incremental processing, automated data loading, and scalable data transformation patterns.
• Design dimensional models and layered warehouse architectures.
• Improve SQL performance, warehouse cost efficiency, and processing reliability.
• Monitor data pipelines, troubleshoot production issues, and maintain data quality.
• Implement data security, access control, and recovery practices.
• Collaborate with engineering and business stakeholders on data requirements and delivery.

Healthcare, Microsoft Windows Azure, Snowflake Schema, Data Management, Data Sets, Data Warehousing, Data Modeling, SQL (Structured Query Language), Scalable System Development, Operational Audit, * Substantial senior-level production data engineering experience, with 10+ years targeted in the formal JD.

• Strong, recent Snowflake engineering expertise.
• Advanced SQL development and performance tuning.
• Enterprise ETL/ELT pipeline implementation experience.
• Hands-on Azure Data Factory and Azure data services.
• Data modeling and cloud data warehouse architecture experience.
• Production troubleshooting, reliability, and data quality expertise.
• Understanding of data governance, privacy, and access controls.
• Git, CI/CD, and collaborative engineering experience.
• Strong problem-solving and communication skills.

PREFERRED EXPERIENCE

• Healthcare claims, payer, or provider data experience.
• Healthcare EDI and medical coding knowledge.
• SQL Server and SSIS modernization.
• Snowpark, stored procedures, or infrastructure-as-code.
• AI-assisted data engineering tools.