Senior Analyst, Analytics -- Enterprise Reporting

Job Description

Job Description

Everlywell is a digital health company pioneering the next generation of biomarker intelligence—combining AI-powered technology with human insight to deliver personalized, actionable health answers. We transform complex biomarker data into life-changing insights—seamlessly integrating advanced diagnostics, virtual care, and patient engagement to reshape how and where health happens.

Over the past decade, Everlywell has delivered close to 1 billion personalized health insights, transforming care for 60 million people and powering hundreds of enterprise partners. In 2025, an estimated 1 in 94 U.S. adults received an Everlywell test, solidifying our spot as the #1 at-home testing company in the country. Fueled by AI and built for scale, we’re breaking down barriers, closing care gaps, and unlocking a more connected healthcare experience that is smarter, faster, and more personalized.

Everlywell is a digital health company pioneering the next generation of biomarker intelligence—combining AI-powered technology with human insight to deliver personalized, actionable health answers. We transform complex biomarker data into life-changing insights—seamlessly integrating advanced diagnostics, virtual care, and patient engagement to reshape how and where health happens.

 

Over the past decade, Everlywell has delivered close to 1 billion personalized health insights, transforming care for 60 million people and powering hundreds of enterprise partners. In 2024 alone, an estimated 1 in 86 U.S. households received an Everlywell test, solidifying our spot as the #1 at-home testing brand in the country. And we’re just getting started. Fueled by AI and built for scale, we’re breaking down barriers, closing care gaps, and unlocking a more connected healthcare experience that is smarter, faster, and more personalized.

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

 

Location Requirement: Candidates must be currently based in Austin, TX, or be willing to relocate to Austin prior to their start date.

What You'll Do:

• 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

Who You Are:

• 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

Nice to Have:

• Experience with a modern data warehouse ((Snowflake, BigQuery, Databricks)
• Familiarity with Python for data validation, automation, or pipeline work
• Prior experience in healthcare, DTC, or a high-growth startup environment

Security Notice : Everlywell never requests fees, payment, or banking information at any stage of the recruitment process. Official communications and interview invitations will only come from verified email addresses ending in @everlywell.com or @everlyhealth.com. To ensure your application is secure, always apply directly through our official careers page at

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.