About the job
ABOUT THE ROLE:
RightWay Healthcare is seeking an innovative Analytics Engineer to contribute to the design and development of a cutting-edge PBM Financial Risk Engine. This engine will integrate claims data, contract terms, pricing, and utilization metrics to enhance financial forecasting, risk evaluation, and performance tracking. The ideal candidate will have a robust background in dbt and analytics engineering, thriving at the crossroads of healthcare economics, PBM operations, and data modeling. You will play a crucial role in shaping and refining our financial risk engine data models, incorporating new data sources, optimizing existing ones, and ensuring that data is presented in a manner that facilitates efficient reporting and drives analytics innovation. This position will involve delivering and analyzing PBM financial data for diverse analytics applications within our Unified Data Warehouse (UDW) and implementing AI and ML solutions to generate impactful healthcare insights.
WHAT YOU’LL DO:
- Utilize your hands-on analytics and data expertise to address complex, dynamic financial and operational challenges using PBM data.
- Design, develop, and maintain scalable, analytics-ready data models (mainly in dbt) that drive the PBM financial risk engine, utilizing claims, eligibility, pricing, rebates, guarantees, and contract data from our Unified Data Warehouse (UDW).
- Transform intricate PBM contract and pricing structures (e.g., plan paid vs. member paid, rebates, guarantees, caps, fees, exclusions) into clear, auditable data models that facilitate financial analysis and risk evaluation.
- Collaborate closely with underwriting, finance, client success, and PBM operations teams to comprehend financial assumptions, risk factors, and reporting needs, converting them into dependable metrics and models.
- Create curated financial and risk data marts and semantic layers that empower self-service analysis for forecasting, scenario modeling, and executive reporting.
- Take ownership of core financial KPIs and risk metrics end-to-end, from raw claims and contract inputs to production-grade models, ensuring consistency and traceability.
- Establish automated data quality checks, reconciliations, and controls to validate financial outputs, ensuring alignment with source systems and contractual logic.
- Continuously enhance data models and warehouse performance to accommodate large-scale claims volumes and time-sensitive financial analyses.
- Contribute to data governance by setting modeling standards, documentation, and guidelines that support auditability, explainability, and long-term maintainability.
- Effectively communicate complex financial insights to stakeholders.

