Analytics Engineer

**Thank you for considering a career at Ensemble!** Ensemble is a leading provider of technology\-enabled revenue cycle management solutions for health systems, including hospitals and affiliated physician groups. They offer end\-to\-end revenue cycle solutions as well as a comprehensive suite of point solutions to clients across the country. Ensemble keeps communities healthy by keeping hospitals healthy. We recognize that healthcare requires a human touch, and we believe that every touch should be meaningful. This is why our people are the most important part of who we are. By empowering them to challenge the status quo, we know they will be the difference! O.N.E Purpose:* **Customer Obsession:** Consistently provide exceptional experiences for our clients, patients, and colleagues by understanding their needs and exceeding their expectations. * **Embracing New Ideas:** Continuously innovate by embracing emerging technology and fostering a culture of creativity and experimentation. * **Striving for Excellence:** Execute at a high level by demonstrating our “Best in KLAS” Ensemble Difference Principles and consistently delivering outstanding results. **The Opportunity:** As an Analytics Engineer, you will play a critical role in advancing Ensemble’s data, automation, and AI strategy within Revenue Cycle Management (RCM). This role focuses on driving end\-to\-end automation of the Accounts Receivable (AR) Follow\-Up function through scalable, production\-grade data models built in a Databricks Lakehouse environment using dbt. Beyond traditional analytics engineering, this role will help lay the foundation for AI\-enabled AR workflows — including intelligent account prioritization, denial pattern detection, predictive insights, and workflow optimization. You will design trusted data products that power both deterministic automation and AI/ML initiatives. We prioritize strong analytics engineering fundamentals, modern data stack expertise, and scalable design practices. Healthcare RCM experience is a strong advantage but not required — domain expertise can be developed. Technical excellence, engineering rigor, and systems thinking are essential. You will partner closely with operations, product, data science, architecture, and engineering leaders to translate AR workflows into reliable, automated, and AI\-ready data solutions that improve operational efficiency and accelerate cash outcomes.**Essential Job Functions** --------------------------- ### **Core Responsibilities** * Design, develop, test, deploy, monitor, and continuously improve high\-quality data models and transformation pipelines using dbt within a Databricks Lakehouse environment. * Build scalable, maintainable, and reusable data models, macros, testing frameworks, and automation logic that address cross\-functional AR Follow\-Up needs. * Collaborate with operational and product stakeholders to translate AR workflows into technical designs and incremental deliverables that enable