Lead Analytics Engineer

Hi, we're Oscar. We're hiring a Lead 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 Lead Analytics Engineer drives the definition of the vision for Oscar's unified analytics data foundation, leading this effort from initial buildout through ongoing operation and continuous expansion of domain coverage and platform capabilities. Oscar is consolidating fragmented legacy data transformation systems that support analytics across the organization into a single dimensionally modeled platform in dbt, and building out an enterprise-wide semantic layer to serve all business analytics use cases. This role requires someone who has played a central role in establishing both a dimensional model and a semantic layer at enterprise scale, and who brings the judgment and experience to ensure Oscar gets both right. The Lead Analytics Engineer is accountable for the design and coherence of the overall dimensional model and semantic layer while also contributing as a hands-on builder. Data consistency, shared definitions, and singular sourcing are the foundations of trustworthy analytics, and this role exists to deliver on that principle.

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: $163,944 - $215,176.50 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 cross-functionally with domain experts and stakeholders to capture business logic and translate it into the unified dimensional model, whether consolidating from existing systems or modeling new domains.
• Define the design standards, patterns, and structure of Oscar's unified dimensional model in dbt, ensuring coherence and extensibility as domain coverage expands across the organization.
• Lead the design and implementation of an enterprise-wide semantic layer that serves all business analytics use cases with consistent, governed definitions.
• Serve as the subject matter expert on dimensional modeling and semantic layer design, guiding the team on best practices and ensuring implementation quality across all business domains.
• Lead cross-functional projects to consolidate, scale, and continuously improve Oscar's analytics data transformation solutions, ensuring they meet business needs efficiently and effectively.
• Ensure the analytics platform and related systems are administered according to industry standards, internal controls are followed, and processes are aligned with established Data Governance principles.
• Ensure data models and semantic layer artifacts are documented and structured to support enterprise data discoverability.
• Design and continuously improve data transformations and semantic layer systems with a focus on performance, cost-effectiveness, and stability.
• Expand the coverage of data quality checks and enhance monitoring and alerting pipelines to ensure the reliability and accuracy of analytics outputs.
• Champion Oscar's culture and values, mentor 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; enable team members to do the same.
• Compliance with all applicable laws and regulations.
• Other duties as assigned.
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Requirements:

• Demonstrated experience playing a central role in establishing a dimensional model and a semantic layer at enterprise scale.
• 6+ years of experience in Analytics Engineering, Data Engineering, or a related field.
• 4+ years of experience working with SQL to transform and model data at scale.
• 4+ years of experience building dimensional models using modern data transformation tools such as dbt.
• 4+ years of experience designing and implementing semantic layers using enterprise business intelligence platforms such as Tableau, Looker, or Power BI.
• 1+ years of people management experience (for people manager roles).

Bonus points:

• Experience in the healthcare and/or insurance industries.
• Experience with Google Cloud Platform.
• Excellent communication skills, verbal and written, as demonstrated by experience on multiple projects or initiatives requiring communication between technical and non-technical users.