The job, in the employer's words
Hi, we're Oscar. We're hiring a Director, Analytics Engineering 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 Director of Analytics Engineering leads the Analytics Engineering function for Oscar Health and sets the enterprise strategy for trusted, governed, reusable data that is well documented, high quality, and ready to support analytics and AI applications. This leader drives 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.
You will report into the VP, Data.
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: $198,720 - $260,820 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, company equity grants, and annual performance bonuses.
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 the engineering standards and operating practices that keep enterprise data products consistent, reliable, observable, and supported by clear production-quality and incident-response practices.
- Build and lead high-performing teams, including managers and senior ICs; 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.
- Compliance with all applicable laws and regulations
- Other duties as assigned
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.
Bonus points:
- Experience in healthcare, insurance, or another regulated environment.
This is an authentic Oscar Health job opportunity.
At Oscar, being an Equal Opportunity Employer means more than upholding discrimination-free hiring practices. It means that we cultivate an environment where people can be their most authentic selves and find both belonging and support. We're on a mission to change health care -- an experience made whole by our unique backgrounds and perspectives.
Pay Transparency: Final offer amounts, within the base pay set forth above, are determined by factors including your relevant skills, education, and experience. Full-time employees are eligible for benefits including: medical, dental, and vision benefits, 11 paid holidays, paid sick time, paid parental leave, 401(k) plan participation, life and disability insurance, and paid wellness time and reimbursements.
Artificial Intelligence (AI): Our AI Guidelines outline the acceptable use of artificial intelligence for candidates and detail how we use AI to support our recruiting efforts.
Reasonable Accommodation: Oscar applicants are considered solely based on their qualifications, without regard to applicant’s disability or need for accommodation. Any Oscar applicant who requires reasonable accommodations during the application process should contact the Oscar Benefits Team (accommodations@hioscar.com) to make the need for an accommodation known.
California Residents: For information about our collection, use, and disclosure of applicants’ personal information as well as applicants’ rights over their personal information, please see our Privacy Policy.
Requirements mentioned
- 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.
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