Business Intelligence Engineer III

Sutter Health•Sacramento, CA

6d•$117,437 - $176,155•Hybrid

About The Position

A mid-level Technical Health Care Analytics professional who exercises independent judgment to architect, engineer, and optimize full-stack data products. This role acts as a technical authority, designing complex, end-to-end decision support systems. They are responsible for the entire product lifecycle: from consultative systems analysis and backend data engineering to frontend application architecture and user experience engineering. Responsible for the full-stack engineering of the department's analytics applications. This role requires the exercise of discretion to solve novel technical problems, such as engineering complex interactivity patterns, optimizing end-to-end application performance, or 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, or equivalent experience.
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 translate complex business problems into engineered solutions.
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.

Nice To Haves

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.
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.
Act as a technical authority, designing complex, end-to-end decision support systems.
Manage the entire product lifecycle: from consultative systems analysis and backend data engineering to frontend application architecture and user experience engineering.
Perform full-stack engineering of the department's analytics applications.
Solve novel technical problems, such as engineering complex interactivity patterns, optimizing end-to-end application performance, or designing custom data integration logic for specific business use cases.
Independently architect and manage the full lifecycle of complex data products (from raw data to finished app).
Design and develop dashboards to communicate complex analytical findings visually to diverse audiences.
Perform data transformation and ETL development (SSIS, ADF) to support reporting needs.
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.