Senior 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.
• Expand the coverage of data quality checks and enhance monitoring and alerting pipelines to ensure the reliability and accuracy of analytics outputs.
• Develop deep expertise in Oscar's analytics technologies, tools, and business domains, contributing to the continuous improvement of Oscar's analytics ecosystem.
• Provide training and mentorship to more junior team members, cultivate a culture of excellence in analytics engineering, and foster continuous skill development.
• Use AI to accelerate development, improve quality, and solve problems.
• Compliance with all applicable laws and regulations.
• Other duties as assigned.

Requirements:

• 4+ years of experience in Analytics Engineering, Data Engineering, or a related field.
• 3+ years of experience working with SQL to transform and model data at scale.
• 2+ years of experience building dimensional models (star schemas, slowly changing dimensions, surrogate key management).
• Experience designing conformed dimensional models spanning 2 or more distinct business domains or processes.
• 2+ years of experience developing within a modern data transformation tool such as dbt.
• 2+ years of experience with cloud data platforms (GCP, AWS, Azure).
• 2+ years of experience partnering with domain experts or stakeholders to translate business requirements into data models.
• Experience using AI tools to accelerate development workflows.

Bonus points:

• Experience designing and implementing semantic layers.
• Experience integrating data from multiple independent source systems into a unified analytical foundation.
• Experience with Google Cloud Platform.
• Experience in the healthcare and/or insurance industries.
• Strong communication skills, verbal and written, as demonstrated by experience on projects or initiatives requiring communication between technical and non-technical users.