Analytics Engineer - Associate

Job Description

Analytics Engineers use industry‑leading analytics, data, and software engineering best practices to deliver on Intermountain Health's mission to help people live the healthiest lives possible, making healthcare more affordable and higher quality, and making a meaningful difference in the patients and communities we serve.

As an Associate Analytics Engineer, you will support the development and maintenance of data pipelines, processes, and analytics solutions across clinical, operational, and pharmacy domains. You will collaborate closely with senior team members to learn and implement best practices in data engineering and analytics, including modern cloud‑based platforms such as Databricks.

Your role will involve enhancing data and system processes using advanced technical methods, supporting pharmacy analytics initiatives such as medication utilization analysis, pharmacy operations reporting, and drug cost optimization. You will quickly learn and apply new tools and techniques to improve analytics and deliver actionable insights.

Please note that a video interview through Microsoft Teams will be required as well as potential onsite interviews and meetings.

We are committed to offering flexible work options where approved and stated in the job posting. However, we are currently not considering candidates who reside or plan to reside in the following states:
California, Connecticut, Hawaii, Illinois, New York, Rhode Island, Vermont, and Washington.

• Assist in the development and maintenance of software solutions and processes.
• Assist in the development and deployment of data pipelines and orchestration, including pipelines built on Databricks.
• Support the creation of data models and analytics solutions for clinical, operational, and pharmacy analytics use cases.
• Collaborate with senior team members to learn and apply best practices in data engineering, cloud analytics, and healthcare data management.
• Help create dashboards and reports for various stakeholders, including pharmacy leadership and medication management teams.
• Perform data quality checks and validation, including pharmacy‑related datasets such as medication orders, dispensing data, and drug cost files.
• Contribute to pharmacy analytics initiatives such as medication adherence reporting, formulary analysis, and pharmacy performance metrics.

• Software Development (Python, JavaScript)
• Structured Query Language (SQL)
• Data Modeling & Design
• Data Visualization
• Data Engineering
• Pharmacy Analytics (medication utilization, drug cost analysis, pharmacy operations reporting)
• Databricks (Delta Lake, notebooks, workflows, cluster management)

• Effective use of data visualization tools (e.g., Tableau, Power BI).
• Strong analytical and problem‑solving skills.
• Excellent communication and teamwork abilities.
• Ability to learn and apply best practices in data engineering and analytics.
• Competent in Python and SQL.
• Familiarity using agile methodologies and version control systems.
• Experience delivering software development solutions.

• A Masters Degree in an analytics‑related field such as information systems, data science / analytics, statistics, computer science, mathematics.
• or
• 2 years of professional experience in an analytics role and a Bachelor's Degree in an analytics-related field such as statistics, mathematics, information systems, computer science, data science / analytics.
• Experience with both backend and frontend software development (Python, Java, JavaScript, JS Frameworks).
• Leveraging Cloud Data platforms including (Databricks, Azure)
• Understanding of effective use of APIs to integrate and extend capabilities of tools and services.
• System infrastructure setup involving Linux, Docker Containers.
• Utilizing No
  
  SQL databases within applications.
• Development of AI based solutions.

• Interact with others by effectively communicating, both orally and in writing.
• Operate computers and other office equipment requiring the ability to move fingers and hands.
• See and read computer monitors and documents.
• Remain sitting or standing for long periods of time to perform work on a…