Analytics Engineer

Analytics Engineer (PBM Financial Risk Engine)

You will design and build a PBM Financial Risk Engine and support financial forecasting, risk assessment, and performance monitoring. The role focuses on data modeling, onboarding and optimizing data sources, and turning complex financial insights into clear metrics for both technical and non-technical stakeholders.

Key missions

• Design and build a PBM Financial Risk Engine integrating multiple data sources for forecasting and risk assessment.
• Develop and maintain financial risk engine data models; onboard new data sources and optimize existing ones for reliable reporting.
• Collaborate with underwriting, finance, client success, and PBM operations to translate financial assumptions into accurate, testable metrics.
• Deliver and analyze PBM financial data and productionalize AI/ML solutions (where applicable).
• Communicate insights and explain complex financial results to stakeholders across technical backgrounds.

Profile / Requirements

• Strong expertise in dbt and analytics engineering.
• Expert-level SQL and statistical programming in Python and/or R.
• Experience with cloud platforms (preferably AWS) and cloud data warehouses such as Redshift or Snowflake.
• Ability to model large-scale claims data and translate contractual/financial rules into clear data logic.
• Business acumen with exposure to PBM, healthcare economics/finance, underwriting, or actuarial concepts.
• High attention to detail with a bias toward accuracy, transparency, and explainability.
• Comfortable partnering with finance/underwriting/operations to ensure data models match real-world decisions.

Nice-to-haves / Expectations

• Experience with analytics engineering best practices: testing, documentation, incremental models, and semantic layers.

Experience

• 3 to 4 years of experience in data modeling, dbt, and analytics engineering best practices.