Analytics Engineer

Hi, we're Oscar. We're hiring a Senior Analytics Engineer to join our Data Team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role:

The Senior Analytics Engineer designs, builds, and maintains conformed dimensional models that convert raw operational data from multiple independent source systems into reliable, well-structured analytical assets spanning multiple business domains. The Senior Analytics Engineer partners with domain experts and stakeholders to capture business logic, resolves cross-source inconsistencies, and translates requirements into Oscar’s unified dimensional model. The Senior Analytics Engineer contributes to shared conventions and standards, mentors more junior team members, uses AI to accelerate development, and operates with high independence on complex modeling work

You will report into the Associate Director, Data Science.

Work Location: This position is based in our New York City office, requiring a hybrid work schedule with 3 days of in-office work per week. Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $149,040 - $195,615 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants, and annual performance bonuses.

Responsibilities:

• Partner with domain experts and stakeholders to understand business logic and translate it into dimensional models within Oscar's unified data foundation.
• Design, build, and maintain conformed dimensional models in dbt spanning multiple business domains, including source-to-target mapping, historical change tracking, and shared dimension governance.
• Resolve cross-source inconsistencies when integrating independently-built upstream systems, ensuring data from different origins conforms to shared definitions and enables analysts to answer questions that span domains.
• Contribute to the design and implementation of semantic layer artifacts that support enterprise business intelligence needs.
• Lead cross-functional mid-to-long term projects focused on optimizing, scaling, and improving analytics data transformation solutions, with a focus on efficiency, cost-effectiveness, and stability.
• Ensure data models and transformations align with established Data Governance principles.