Epic BI Data Engineer - Cloud ETL & Analytics

University Health; San Antonio (TX); On-site; USD 110,000 - 160,000; Full time

Job summary

University Health is seeking an Epic Business Intelligence Data Engineer to design and support data pipelines, models, and analytic infrastructure across Epic, SQL Server, and cloud platforms. This role develops trusted data assets for operational reporting, quality improvement, population health, and financial analysis.

You will build ETL/ELT pipelines, support Clarity, Caboodle, and data lakes, ensure data quality and governance alignment, and work with BI analysts and application teams to

Qualifications

• Bachelor's degree in IT, CS, data engineering or related field is required.
• Master's degree preferred; cloud certifications in Azure, AWS or Google required.
• 8+ years of SQL and SQL Server experience required.
• Experience with ETL tools, data engineering frameworks, and cloud platforms required.
• Healthcare environment or Epic ecosystem experience preferred.

Responsibilities

• Design and support data pipelines, data models, and analytic infrastructure across Epic, SQL Server, and cloud platforms.
• Build high-quality, trusted data assets for operational reporting, quality improvement, and financial analysis.
• Design, build, test, and optimize ETL/ELT pipelines and data environments like Clarity and Caboodle.
• Collaborate with BI analysts and end users to meet enterprise reporting needs.

Skills

SQL

ETL tools

Cloud platforms

Data modeling

Healthcare data

Education

Bachelor's degree

Master's degree preferred

Tools

Azure

AWS

Google Cloud

Epic Clarity

Epic Caboodle

Job description

University Health is seeking an Epic Business Intelligence Data Engineer to design and support data pipelines, models, and analytic infrastructure across Epic, SQL Server, and cloud platforms. This role develops trusted data assets for operational reporting, quality improvement, population health, and financial analysis.

You will build ETL/ELT pipelines, support Clarity, Caboodle, and data lakes, ensure data quality and governance alignment, and work with BI analysts and application teams to