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 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 valuer.
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
Required Skills & Experience
- Bachelor’s degree in computer science, Engineering, Mathematics, Statistics, or related technical field.
- 3+ 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 architectures.
- Strong communication skills with the ability to translate complex technical concepts to diverse stakeholders.
- Demonstrated curiosity and interest in enabling AI, ML, or intelligent automation initiatives.
- Demonstrated knowledge of data architecture principles, modeling patterns, and analytics engineering best practices.
Preferred (Strongly Valued but Not Required)
- Experience working with healthcare revenue cycle management data (claims, remittances, denials, payments, AR aging).
- Familiarity with AR Follow-Up workflows, operational work queues, or denial management processes.
- Experience supporting automation, workflow optimization, or rule-based systems.
- Exposure to ML feature engineering, model enablement, or AI-driven insights within Databricks.
- Experience working in regulated industries requiring strong data governance and compliance controls.
Join an award-winning company
Five-time winner of “Best in KLAS” 2020-2022, 2024-2025
Black Book Research's Top Revenue Cycle Management Outsourcing Solution 2021-2024
22 Healthcare Financial Management Association (HFMA) MAP Awards for High Performance in Revenue Cycle 2019-2024
Leader in Everest Group's RCM Operations PEAK Matrix Assessment 2024
Clarivate Healthcare Business Insights (HBI) Revenue Cycle Awards for strong performance 2020, 2022-2023
Energage Top Workplaces USA 2022-2024
Fortune Media Best Workplaces in Healthcare 2024
Monster Top Workplace for Remote Work 2024
Great Place to Work certified 2023-2024
Innovation
Work-Life Flexibility
Leadership
Purpose + Values
Bottom line, we believe in empowering people and giving them the tools and resources needed to thrive. A few of those include:
Associate Benefits – We offer a comprehensive benefits package designed to support the physical, emotional, and financial health of you and your family, including healthcare, time off, retirement, and well-being programs.
Our Culture – Ensemble is a place where associates can do their best work and be their best selves. We put people first, last and always. Our culture is rooted in collaboration, growth, and innovation.
Growth – We invest in your professional development. Each associate will earn a professional certification relevant to their field and can obtain tuition reimbursement.
Recognition – We offer quarterly and annual incentive programs for all employees who go beyond and keep raising the bar for themselves and the company.
Ensemble is an equal employment opportunity employer. It is our policy not to discriminate against any applicant or employee based on race, color, sex, sexual orientation, gender, gender identity, religion, national origin, age, disability, military or veteran status, genetic information or any other basis protected by applicable federal, state, or local laws. Ensemble also prohibits harassment of applicants or employees based on any of these protected categories.
Ensemble provides reasonable accommodations to qualified individuals with disabilities in accordance with the Americans with Disabilities Act and applicable state and local law. If you require accommodation in the application process, please contact TA@ensemblehp.com.
This posting addresses state specific requirements to provide pay transparency. Compensation decisions consider many job-related factors, including but not limited to geographic location; knowledge; skills; relevant experience; education; licensure; internal equity; time in position. A candidate entry rate of pay does not typically fall at the minimum or maximum of the role’s range.