Analytics Engineer
Ensemble Health Partners
full-time
Posted on:
Location Type: Remote
Location: United States
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About the role
- 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 Account prioritization and scoring, Denial categorization and trend analysis, Aging analysis and performance tracking, Workflow routing and automation logic.
Requirements
- 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.
Benefits
- Health insurance
- Time off
- Retirement programs
- Professional development
- Awards for performance
- Well-being programs
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
dbtDatabricksSparkDelta LakeSQLdata modelingdata transformationautomated testingCI/CDanalytics engineering
Soft Skills
communicationcollaborationmentoringproblem-solvingcuriositystakeholder engagementleadershipfeedbacktranslating technical conceptscontinuous improvement
Certifications
Bachelor's degree in computer scienceBachelor's degree in EngineeringBachelor's degree in MathematicsBachelor's degree in Statistics