Director, Analytics Engineering

Oscar Health•New York, NY

2d•$198,720 - $260,820•Hybrid

About The Position

Oscar is hiring a Director of Analytics Engineering to lead the Analytics Engineering function and set enterprise strategy for trusted, governed, reusable data that is well documented, high quality, and ready to support analytics and AI applications. The role will drive an enterprise-wide transformation of data practices, platforms, and operating models to improve the speed, reliability, and adoption of self-service analytics and responsible AI use. The Director will own delivery of the analytics engineering operating plan through a multi-team organization, build and govern the enterprise data transformation layer, establish engineering standards and operating practices, and build high-performing teams. The role will partner with business and technology leaders, expand self-service analytics, measure and improve data trust and delivery outcomes, and communicate progress and investment needs to executive stakeholders. This position reports to the VP, Data. The position is based in Oscar’s New York City office and follows a hybrid schedule requiring three in-office days per week. Thursdays are required for team meetings and events; the other two office days are flexible. The base salary is $198,720–$260,820 per year. The role is also eligible for employee benefits, Oscar’s unlimited vacation program, company equity grants, and annual performance bonuses.

Requirements

10+ years of progressive experience in analytics engineering, data engineering, or related technical roles.
5+ years leading multi-team data, analytics, or engineering organizations and developing managers and senior technical talent.
Demonstrated success leading complex, cross-functional data or technology transformations across multiple teams or at enterprise scale.
Deep experience with SQL, dimensional modeling, data modeling, cloud data platforms, and modern transformation, semantic modeling, and data observability tools.
Experience with dbt, Looker, Google Cloud Platform, or comparable technologies.
Experience enabling analytics, machine learning, or generative AI with governed, reusable data products.
Experience with data governance, quality, metadata, lineage, access, data-product ownership, and lifecycle practices.
Ability to influence executive and non-technical stakeholders through clear strategy, communication, and measurable outcomes.

Nice To Haves

Experience in healthcare, insurance, or another regulated environment.

Responsibilities

Own delivery of the analytics engineering operating plan through a multi-team organization, setting the strategy and operating model that make trusted, reusable data easier to build and use.
Build and govern the enterprise data transformation layer that enables trusted analytics and AI, with clear ownership, definitions, quality, lineage, and secure access.
Establish engineering standards and operating practices that keep enterprise data products consistent, reliable, observable, and supported by production-quality and incident-response practices.
Build and lead high-performing teams, including managers and senior individual contributors; set priorities, accountability, organization design, and growth paths.
Partner with business and technology leaders to align operating-plan priorities, investments, and delivery across the enterprise.
Expand self-service analytics by improving the tools, guidance, and support that help people use data confidently.
Measure and improve data trust, delivery speed, self-service adoption, reliability, and cost efficiency.
Represent the function in operating-plan and quarterly business reviews, communicating progress, risks, investment needs, and outcomes to executive stakeholders.
Comply with all applicable laws and regulations.
Perform other duties as assigned.