Senior Analytics Engineer

The Analytics Engineer will support data, automation, and AI initiatives focused on Revenue Cycle Management (RCM), with an emphasis on automating the Accounts Receivable (AR) Follow-Up function. This role will design scalable, production-grade data models using dbt in a modern cloud-based lakehouse environment.

In addition to core analytics engineering responsibilities, this position will help enable AI-driven workflows such as intelligent account prioritization, denial trend detection, predictive insights, and workflow optimization. The ideal candidate brings strong analytics engineering fundamentals, modern data stack experience, and a systems-oriented mindset.

Responsibilities

• Design, build, test, and maintain high-quality data models and transformation pipelines using dbt in a distributed data environment.

• Develop scalable, reusable, and well-tested data models, macros, and automation logic supporting AR Follow-Up workflows.

• Partner with operations, product, and engineering stakeholders to translate business workflows into reliable, automated data solutions.

• Establish and follow analytics engineering standards, including modeling conventions, testing practices, and documentation.

• Participate in technical design discussions, architecture reviews, and code reviews to ensure data quality and long-term scalability.

• Troubleshoot and resolve complex data issues across ingestion, transformation, and reporting layers.

• Optimize data tables and processing workloads for performance, scalability, and cost efficiency.

• Support datasets enabling account prioritization, denial analysis, aging performance, and workflow automation.

Experience with healthcare RCM data (claims, denials, payments, AR aging).

• Familiarity with AR Follow-Up workflows or denial management processes.

• Experience supporting automation, workflow optimization, or rule-based systems.

• Exposure to ML feature engineering or AI-enabled analytics.

• Experience in regulated or compliance-driven environments. - Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.

• 5+ years of experience in analytics engineering, data engineering, or advanced BI roles.

• Strong hands-on experience with dbt or similar ELT frameworks.

• Experience with distributed data platforms such as Databricks, Spark, or equivalent.

• Advanced SQL skills and experience working with large-scale data transformations.

• Solid understanding of analytics engineering best practices, including automated testing, CI/CD, and data governance.

• Strong communication skills and ability to work cross-functionally.

• Interest in supporting AI, ML, or intelligent automation initiatives.