Analytics Engineer - IT AI and Data Technology

St. Peter's Health; Helena (MT); On-site; USD 90,000 - 120,000; Full time

Job summary

St. Peter’s Health in Helena, MT is hiring an Analytics Engineer (IT AI and Data Technology) to translate enterprise data into dashboards, reports, and certified datasets that support clinicians, leaders, and staff.

You will own analytics products, design and maintain semantic models, and collaborate across data pipelines and analytics intake to ensure reliable production use. This onsite role emphasizes healthcare analytics expertise, KPI definition with stakeholders, and clear documentation

Qualifications

• Bachelor's degree in a related field preferred.
• Experience in analytics, business intelligence, reporting, or data analysis.
• Healthcare analytics domain knowledge is a plus.

Responsibilities

• Own the build side of analytics products for one or more domains (clinical care, revenue cycle, operations).
• Collaborate with data pipelines teams and analytics intake/shared definitions teams.

Skills

SQL

Power BI

Python

Semantic Layer

Data modeling

Data quality

Production support

Education

Bachelor’s degree

Associate degree

Master’s degree

Tools

Epic Clarity

Caboodle

Cogito

Snowflake

dbt

Git

Job description

St. Peter’s Health is hiring an Analytics Engineer (IT AI and Data Technology) to translate enterprise data into dashboards, reports, certified datasets, and shared semantic models. These analytics products support clinicians, leaders, and staff in improving care delivery, operational performance, and financial outcomes.

Onsite Location

Helena, MT (onsite)

Core Responsibilities

• Own the build side of analytics products for one or more assigned domains, such as clinical care, revenue cycle, or operations. This includes designing, developing, certifying, and maintaining analytics products so they remain accurate, documented, and reliable for daily production use.
• Collaborate with teams that operate data pipelines and teams that steward analytics intake and shared definitions.

Experience & Level Expectations

• Level I: two or more years of relevant experience.
• Level II: four or more years of relevant experience.
• Level III: six or more (progressive) years of relevant experience.

Relevant experience may include analytics, business intelligence, reporting, or data analysis, or an equivalent combination of education and experience.

Technical Requirements

• Working knowledge of SQL and at least one BI or reporting tool at Level I; progression to proficiency with at least one modern BI platform at Level II (including Power BI as preferred).
• At Level III, advanced SQL and semantic layer proficiency.
• Experience at Level I supporting dashboards, reports, curated datasets, or data validation; at Level II, independently delivering these and managing stakeholder relationships; at Level III, demonstrated healthcare analytics domain expertise, including defining KPIs with business owners.
• Foundational understanding of data modeling, data quality, and production support concepts at Level I.
• Working exposure to Python at Level II; Python proficiency at Level III, including strong command of dataset certification and production support practices.
• Clear documentation and communication skills at every level, with progression to leading technical design, mentoring others, and presenting clearly to clinical and executive audiences at Level III.

Relevant Technologies

• SQL, Power BI, Python, semantic layer
• Epic Clarity, Caboodle, Cogito
• Snowflake, dbt, Git
• ICD-10, CPT, HEDIS, HL7/FHIR

Preferred Background

• 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, along with familiarity with healthcare data standards such as ICD-10, CPT, HEDIS, and HL7/FHIR.
• Familiarity with HIPAA and healthcare data privacy and security practices, including 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.

Licensing and Certifications

• 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.