Jobs · Analyst · Massachusetts

Senior Manager, Analytics Engineering

WHOOP · Boston, MA · 1 mo ago
On-siteAnalyst$210k–$245k/yrFull-time

Responsibilities

  • Own the WHOOP Analytics data model end-to-end, partnering with analysts and business stakeholders to ensure data is modeled to answer key business questions and serve as a single source of truth.
  • Hire, manage, coach, and develop a team of Analytics Engineers, driving high performance, career growth, and a culture of technical excellence.
  • Serve as the primary conduit between Analytics and Data Platform Engineering, aligning on shared infrastructure, data contracts, and pipeline architecture.
  • Own and evolve WHOOP's semantic layer, ensuring consistency and accuracy of key metrics across all downstream tools and consumers.
  • Define and enforce coding standards, documentation practices, and development processes (CI/CD, code reviews, testing requirements, data quality monitoring).
  • Lead strategic data initiatives spanning multiple teams and business outcomes, from scoping through execution.
  • Maintain strong knowledge of industry trends and tooling developments; evaluate and introduce technologies that improve team leverage — including AI-assisted development and data tooling.
  • Partner with Analytics leadership and cross-functional teams to build and evolve the data strategy at WHOOP.
  • Interface with senior leadership to design, plan, and communicate data strategy and roadmap.

Qualifications

  • 7+ years of experience in analytics engineering, data engineering, or a related field, with at least 2 years of people management experience.
  • Deep expertise in SQL, dbt, and Snowflake; strong understanding of dimensional modeling and data warehouse design patterns.
  • Experience building and leading high-performing data teams, including hiring, mentoring, and setting technical direction.
  • Hands-on proficiency with modern data stack tooling (dbt, Snowflake, Sigma or similar BI tools, Git, Python).
  • Demonstrated ability to bridge technical and business stakeholders — translating business requirements into data architecture decisions and communicating trade-offs clearly.
  • Track record of owning and delivering large-scale data initiatives with measurable business outcomes.
  • Excellent communication and stakeholder management skills, particularly in interfacing with senior leadership.

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