Analytics Engineer

Ensemble is seeking an Analytics Engineer to advance their data, automation, and AI strategy within Revenue Cycle Management. The role focuses on driving end-to-end automation of the Accounts Receivable Follow-Up function through scalable, production-grade data models built in a Databricks Lakehouse environment using dbt.

Requirements

• 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.
• 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.

Benefits

• Comprehensive benefits package
• Time off
• Retirement and well-being programs