Business Intelligence Engineer III

Sutter Health•Sacramento, CA

7d•Hybrid

About The Position

This role is for a mid-level Technical Health Care Analytics professional at Sutter Health, specifically within the SHSO-Sutter Health System Office-Valley. The position requires a minimum of 2 days onsite in Sacramento, California. The engineer will exercise independent judgment to architect, engineer, and optimize full-stack data products, acting as a technical authority in designing complex, end-to-end decision support systems. Responsibilities include managing the entire product lifecycle, from consultative systems analysis and backend data engineering to frontend application architecture and user experience engineering. The role involves solving novel technical problems, such as engineering complex interactivity patterns, optimizing application performance, and designing custom data integration logic for specific business use cases.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field (equivalent experience will be accepted).
Epic Cogito Certification within one year of start date.
One tool-specific certification (Microsoft Certified: Power BI Data Analyst Associate OR Tableau Certified Data Analyst) within one year of start date.
3 years of progressive experience in BI Engineering, Data Product Development, or Full Stack Analytics.
Experience independently architecting and managing the full lifecycle of complex data products (from raw data to finished app).
Experience in Dashboard design and development to communicate complex analytical findings visually to diverse audiences.
Experience in data transformation and ETL development (SSIS, ADF) to support reporting needs.
Demonstrated experience working with health care data systems.
Strong proficiency in both Tableau and Power BI, including advanced interactivity and complex DAX/LOD expressions.
Advanced SQL skills, including deep execution plan analysis and query optimization for visualization tools.
Advanced proficiency in BI Application Engineering (Tableau & Power BI), including complex calculations (LODs, DAX) and performance tuning.
Expert SQL; Advanced DAX or M (Power Query).
Ability to move fluidly between backend data engineering (SQL/ETL) and frontend application design (Viz/UX).
Familiarity with CI/CD pipelines for BI (e.g., Azure DevOps, Tabular Editor) and version control (Git).
Excellent technical communication skills.
Ability to work independently, manage multiple complex projects, and define technical strategy.
Demonstrated ability to articulate complex analytical findings, business requirements, metrics, and recommendations clearly to both technical and non-technical stakeholders.
Ability to quickly understand and evaluate new data sources, determine business relevance, assess data quality, and transform complex data into actionable insights, meaningful metrics, KPIs, and reporting solutions that support strategic, operational, and clinical decision-making.

Nice To Haves

Prior Epic Clarity, Cogito experience preferred.
Prior knowledge of Health Care data & concepts preferred.
Familiarity with Diagnosis & Procedure Data, Population Health Management, Risk Adjustment (RAF), HEDIS, Pay-for-Performance (P4P), Quality Measurement, Value-Based Care, and regulatory reporting.

Responsibilities

Architect, engineer, and optimize full-stack data products.
Design complex, end-to-end decision support systems.
Manage the entire product lifecycle: consultative systems analysis, backend data engineering, frontend application architecture, and user experience engineering.
Engineer complex interactivity patterns.
Optimize end-to-end application performance.
Design custom data integration logic for specific business use cases.
Full-stack engineering of the department's analytics applications.
Dashboard design and development to communicate complex analytical findings visually to diverse audiences.
Data transformation and ETL development (SSIS, ADF) to support reporting needs.
Translate complex business problems into engineered solutions.
Articulate complex analytical findings, business requirements, metrics, and recommendations clearly to both technical and non-technical stakeholders.
Quickly understand and evaluate new data sources, determine business relevance, assess data quality, and transform complex data into actionable insights, meaningful metrics, KPIs, and reporting solutions that support strategic, operational, and clinical decision-making.