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 a Senior Analytics Engineer, you will play a critical role in advancing Ensemble’s data, automation, and AI strategy within Revenue Cycle Management (RCM).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.

Essential Job Functions 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 automation and intelligent prioritization.

Partner with data architecture to establish, document, and advocate for analytics engineering standards, modeling conventions, naming patterns, and testing best practices.

Participate in and help lead technical design sessions, spike investigations, and data architecture reviews to ensure alignment with long-term platform and automation strategy.

Engage in code reviews to ensure data model quality, promote modular and testable design, and mentor engineers through constructive, actionable feedback.

Troubleshoot complex data issues across ingestion, transformation, and semantic layers, driving sustainable, long-term fixes.

Contribute to a culture of analytics engineering excellence by promoting automation, observability, data quality testing, governance, and continuous improvement.

Design and optimize Delta Lake tables and Spark workloads for performance, scalability, and cost efficiency.

Help evaluate emerging tools, frameworks, and vendor solutions within the modern data ecosystem and provide guidance on their potential impact or value.

Support the transformation of AR Follow-Up through structured datasets that enable (for example):

Account prioritization and scoring

Denial categorization and trend analysis

Aging analysis and performance tracking

Workflow routing and automation logic

Qualifications

Bachelor’s degree in computer science, Engineering, Mathematics, Statistics, or related technical field.
5+ years of experience in analytics engineering, data engineering, or advanced BI building production-grade data solutions.

Strong hands-on experience with dbt in a modern ELT environment (or similar framework).Experience working with Databricks, Spark, and Delta Lake (or similar distributed data platforms).Advanced SQL expertise and experience optimizing large-scale data transformations.

Deep understanding of analytics engineering best practices including automated testing, CI/CD, modular design, observability, and governance.

Experience building scalable data models in distributed or cloud-based…