Analytics Engineering Solutions Architect

Overview

Responsible for designing and implementing advanced analytics solutions that drive data-driven decision-making across the organization. This position collaborates with cross-functional teams, including data engineers, data scientists, analytics engineers and business stakeholders, to understand requirements and translate them into robust analytical frameworks including self-service solutions in Epic, Health Catalyst and Azure Services.

 

Remote/work from home with strong preference for candidates residing within the UPH geographies of Iowa, Illinois, & Wisconsin.

Why UnityPoint Health?

At UnityPoint Health, you matter. We’re proud to be recognized as a Top 150 Place to Work in Healthcare by Becker's Healthcare several years in a row for our commitment to our team members.  

Our competitive Total Rewards program offers benefits options that align with your needs and priorities, no matter what life stage you’re in.  Here are just a few:      

• Expect paid time off, parental leave, 401K matching and an employee recognition program.   

• Dental and health insurance, paid holidays, short and long-term disability and more. We even offer pet insurance for your four-legged family members.  

• Early access to earned wages with Daily Pay, tuition reimbursement to help further your career and adoption assistance to help you grow your family.   

With a collective goal to champion a culture of belonging where everyone feels valued and respected, we honor the ways people are unique and embrace what brings us together.   

And, we believe equipping you with support and development opportunities is a vital part of delivering an exceptional employment experience. 

Find a fulfilling career and make a difference with UnityPoint Health.

Responsibilities

• Design and maintain enterprise analytics assets, including curated data models, semantic layers, business metric definitions, and reusable reporting components that support self-service analytics.
• Provide technical leadership and architectural oversight for enterprise analytics initiatives, ensuring alignment with organizational strategy, data governance standards, and platform roadmaps.
• Partner with data governance, compliance, and security teams to ensure analytics solutions meet organizational standards for data quality, privacy, auditability, and regulatory requirements.
• Experience supporting healthcare analytics, including clinical, operational, financial, and quality reporting initiatives preferred.
• Evaluate incoming analytics requests and recommend appropriate solutions, including Epic-native tools, enterprise reporting platforms, self-service capabilities, or custom development approaches.
• Lead efforts to promote self-service analytics by identifying opportunities to leverage Epic-native tools, reduce redundant reporting solutions, and improve data accessibility for business users.
• Facilitate discussions among executive, operational, clinical, and technical stakeholders to align on analytics priorities, solution approaches, and implementation strategies.
• Serves as the enterprise technical leader for Epic analytics architecture, including Clarity, Caboodle, Cogito tools, Health Catalyst, and Azure analytics platforms.
• Provides technical direction and mentorship to analytics engineers and developers while establishing enterprise reporting standards and best practices.
• Leads evaluation of reporting requests and promotes Epic-native self-service solutions whenever feasible before custom development approaches are considered.

Qualifications

Education:

• Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field required.

• Master’s degree in a related field preferred.

Certifications:

• Cogito Fundamentals certification required.

• Caboodle Data Model and Clarity Data Model certifications required.

• At least one role-relevant data model certification in one of the following areas required:

  • Clinical

  • Revenue

  • Patient Access

Experience:

• Three (3) years of experience with data warehousing and programming languages, including Python and R, required.

• Two (2) years of experience with data integration platforms and cloud platforms, such as AWS, Azure, or Google Cloud, required.

• One (1) year of experience with cloud storage solutions (e.g., AWS S3, Azure Blob Storage), version control tools (e.g., Git), and Agile methodologies required.

• Two (2) years of experience with analytical tools and libraries (e.g., Pandas, NumPy, Scikit-learn) and statistical analysis tools (e.g., SAS, SPSS) preferred.

• One (1) year of experience with RESTful APIs and API tools (e.g., Postman, Apigee) preferred.