Senior Analyst, Analytics — Enterprise Reporting

Everlywell

Job Location:

Austin, TX - USA

Monthly Salary: Not Disclosed

Posted on: Yesterday

Vacancies: 1 Vacancy

Job Summary

Everlywell is a digital health company pioneering the next generation of biomarker intelligencecombining AI-powered technology with human insight to deliver personalized actionable health answers. We transform complex biomarker data into life-changing insightsseamlessly 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 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 were breaking down barriers closing care gaps and unlocking a more connected healthcare experience that is smarter faster and more personalized.

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 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 were just getting started. Fueled by AI and built for scale were 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. Youll 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

What Youll 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 doesnt live in one persons 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
Bachelors 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 @ or @. To ensure your application is secure always apply directly through our official careers page at 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.

Required Experience:

Senior IC

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. Youll 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

What Youll 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 doesnt live in one persons 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
Bachelors 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