Senior Analyst, Everly Health

• 4 to 6 years of experience in analytics, business intelligence, or data analytics roles
• Bachelor's degree in a quantitative field (Statistics, Economics, Computer Science, or related) or equivalent experience
• Strong SQL skills; comfortable writing and optimizing complex queries against large datasets
• Hands-on experience with DBT for data modeling and transformation (required)
• Proficiency with a BI tool such as Omni, Looker, or Tableau — including building, maintaining, and scaling dashboards for a broad user base
• Demonstrated ability to build self-serve reporting systems, not just deliver one-off analyses
• Strong data modeling instincts — able to design schemas and metrics layers that hold up as the business scales
• Excellent communication skills; able to work directly with business stakeholders to translate ambiguous needs into clear data solutions
• Detail-oriented, with a track record of owning data quality and consistency across reporting

Desirable

• We are hiring a Senior Analyst with 4 to 6 years of experience to own enterprise reporting for Everlywell
• This role sits within the Analytics team, reporting to the Head of Analytics, and is responsible for building and maintaining the reporting layer that business teams rely on to make decisions — with a strong bias toward self-serve architecture over one-off, request-driven analysis
• You'll build durable, well-modeled data assets that teams across the company can use on their own, rather than fielding recurring requests or depending on Data Engineering to surface data
• Own enterprise reporting end-to-end: define requirements, model the data, build the dashboards, and maintain them over time
• Build and maintain dbt models that create a reliable, well-documented semantic layer for reporting across the business
• Develop and maintain dashboards and self-serve reporting tools (Omni/Looker/Tableau) that reduce ad hoc requests and let stakeholders answer their own questions
• Partner with Data Engineering on data pipeline and warehouse structure to ensure reporting is built on trustworthy, scalable foundations — not workarounds
• Establish and enforce definitions, metrics, and reporting standards so numbers are consistent across teams and dashboards
• Audit and rationalize existing reports and dashboards to reduce redundancy and reporting drift
• Partner with cross-functional stakeholders (Product, Marketing, Ops, Finance) to understand reporting needs and translate them into scalable data models
• Troubleshoot data quality and discrepancy issues, tracing them back to source and fixing at the model level
• Document data models, metric definitions, and reporting logic so institutional knowledge doesn't live in one person's head
• Own a high-visibility function that shapes how the entire company sees and understands its own data
• Direct partnership with the Head of Analytics and exposure to cross-functional leadership
• Growth opportunities within a mission-driven organization investing in scalable, self-serve data infrastructure