Senior Revenue Operations Analyst, Data Quality
Navan INC - New York, NY
Posted Sep 16, 2025
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
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- 401(k) match
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Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Senior Revenue Operations Analyst, Data Quality New York, NY Navan is modernizing the infrastructure of business travel, expense, and spend management - and data is central to that mission. We are seeking a Senior Revenue Operations Analyst, Data Quality to own the integrity and trustworthiness of our go-to-market data, enabling Sales, Marketing, and Revenue Operations to move faster and smarter. In this role, you'll be responsible for identifying, measuring, and improving the quality of GTM data across systems, with a focus on solving problems at the point of data creation. You'll also own the integration and management of third-party data sources into our CRM, ensuring consistency, accuracy, and usability across the GTM tech stack. You'll partner cross-functionally with system owners, data analysts, and operations teams to build scalable data quality practices that support revenue growth and operational excellence. This is a high-impact role for someone who thrives on getting into the details of complex data problems while building processes and tooling that scale. What You'll Do: Own all phases of GTM data quality projects from project planning through execution and completion Define and maintain data quality rules, standards, metrics, and processes, including ROI calculations Build Data Quality dashboards and other methods to measure and report on data quality Lead the integration and maintenance of 3rd party data sources into our CRM , ensuring proper mapping, deduplication, and usage across systems Work cross-functionally to identify and fix data quality issues using sustainable and best-practice tools and processes Maintain a backlog of
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