Analytics Engineer - IT AI and Data Technology
St. Peter's Health Regional Medical Center Helena, Montana, United States
Hospitals and Health Care · 1,001-5,000 employees
About the role
The Analytics Engineer develops and maintains dashboards, reports, and certified datasets to support clinical and operational performance. They collaborate with data pipeline teams to ensure data accuracy, documentation, and reliability in production environments.
What they look for
Requirements
Candidates should have relevant experience in analytics or business intelligence, with proficiency in SQL and modern BI platforms like Power BI. A bachelor's degree in a technical or analytical field is preferred, along with experience in healthcare data models and standards.
Full description
The Analytics Engineer turns trusted enterprise data into dashboards, reports, certified datasets, and shared semantic models that clinicians, leaders, and staff use to improve care, operations, and financial performance. The role owns the build side of analytics products for one or more assigned domain(s) such as clinical care, revenue cycle, or operations — designing, developing, certifying, and keeping those products accurate, documented, and reliable in daily production use — and works closely with the teams that operate data pipelines and that steward analytics intake and shared definitions.
KNOWLEDGE/EXPERIENCE: Required:
- Relevant experience in analytics, business intelligence, reporting, or data analysis, or an equivalent combination of education and experience: two or more years for Level I, four or more for Level II, six or more (progressive) for Level III.
- Working knowledge of SQL and at least one BI or reporting tool at Level I, growing to proficiency with at least one modern BI platform (Power BI preferred) at Level II, and advanced SQL and semantic layer proficiency at Level III.
- Experience supporting dashboards, reports, curated datasets, or data validation at Level I; a track record of independently delivering these and managing stakeholder relationships at Level II; and demonstrated healthcare analytics domain expertise, including defining KPIs with business owners, at Level III.
- Foundational understanding of data modeling, data quality, and production support concepts at Level I, working knowledge with exposure to Python at Level II, and Python proficiency with strong command of dataset certification and production support practices at Level III.
- Clear documentation and communication skills at every level, growing to demonstrated ability to lead technical design, mentor others, and present clearly to clinical and executive audiences at Level III.
Preferred:
- Healthcare provider, payer, or health system experience, including Epic Clarity, Caboodle, or Cogito data models.
- Power BI or a comparable modern BI platform; Snowflake or a comparable cloud data platform.
- Python, dbt, Git, or similar analytics engineering tools; healthcare data standards such as ICD-10, CPT, HEDIS, and HL7/FHIR.
- Familiarity with HIPAA and healthcare data privacy and security practices; responsible use of AI-enabled productivity tools.
EDUCATION:
- Bachelor’s degree in Computer Science, Computer Information Systems, Data Analytics, Health Informatics, Engineering, Mathematics, Statistics, Business Analytics, or a related field is preferred.
- In the absence of a bachelor’s degree, an associate degree or relevant professional certifications with additional years of relevant experience may be accepted (four or more years at Level I, six or more at Level II, eight or more at Level III).
- A master’s degree in a related field may substitute for a portion of the required experience. Equivalent combinations of education, certification, and directly relevant experience will be considered.
LICENSE/CERTIFICATION/REGISTRY:
- No license required.
- Preferred certifications include Microsoft credentials for Power BI or Fabric analytics; Epic Cogito, Clarity, or Caboodle certification or accreditation; SnowPro or a comparable cloud data platform certification; dbt or comparable analytics engineering credentials; or healthcare data analytics credentials such as the AHIMA CHDA.
