St. Peter’s Health uses enterprise analytics to support better care, stronger operations, and improved financial performance. In this onsite role in Helena, MT, you will help clinicians, leaders, and staff trust the data they rely on by building and certifying dashboards, reports, curated datasets, and shared semantic models. You will partner with teams that manage data pipelines and stewardship of analytics intake and shared definitions.
What you’ll be building
The Analytics Engineer owns the build side of analytics products for assigned domains such as clinical care, revenue cycle, or operations. Deliverables are designed for daily production use, with a focus on accuracy, documentation, and reliability. You will also work with pipeline and data stewardship teams to ensure analytics intake and shared definitions stay consistent across the organization.
Responsibilities
- Own the build side of analytics products for one or more assigned domain(s) (clinical care, revenue cycle, or operations), including designing, developing, certifying, and maintaining products that remain accurate, documented, and dependable in daily production use.
- Collaborate with teams responsible for data pipelines and analytics intake, including stewardship of shared definitions.
Requirements
Experience level (Level I, II, III) is based on years of relevant analytics/business intelligence/reporting/data analysis experience or an equivalent combination of education and experience: 2+ years (Level I), 4+ years (Level II), 6+ years (progressive) (Level III).
- SQL and a BI/reporting tool: Level I includes working knowledge; Level II grows to proficiency with a modern BI platform (with Power BI preferred); Level III requires advanced SQL and semantic layer proficiency.
- Analytics deliverables: Level I supports dashboards, reports, curated datasets, or data validation; Level II includes independently delivering these and managing stakeholder relationships; Level III includes demonstrated healthcare analytics domain expertise, including defining KPIs with business owners.
- Data modeling, data quality, and production support: Level I includes foundational understanding; Level II includes working knowledge with exposure to Python; Level III includes Python proficiency and strong command of dataset certification and production support practices.
- Documentation and communication: clear documentation and communication at every level, progressing to leading technical design, mentoring others, and presenting clearly to clinical and executive audiences at Level III.
Tools and technologies
You will work with SQL, Power BI, Python, the semantic layer, and healthcare and analytics ecosystems including Epic Clarity, Caboodle, Cogito, Snowflake, dbt, Git, ICD-10, CPT, HEDIS, and HL7/FHIR.
Preferred qualifications
- 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/security practices; responsible use of AI-enabled productivity tools.
Education
- A Bachelor’s degree in Computer Science, Computer Information Systems, Data Analytics, Health Informatics, Engineering, Mathematics, Statistics, Business Analytics, or a related field is preferred.
- If a bachelor’s degree is not available, 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.
Licenses, certifications, and registry
- No license required.
- Preferred certifications include Microsoft credentials for Power BI or Fabric; 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.
