Peloton is at the forefront of connected fitness, with a powerful and thriving community of over 6.7 million Members across the US, UK, Canada, Germany, and Australia.

Peloton brings together the best equipment, software, content, and instructors to make fitness accessible, effective, and convenient for everyone, while fostering the social connections that keep our Members motivated and moving towards their goals.

Through its immersive fitness ecosystem, Peloton is transforming the way people work out with a vast library of live and on-demand studio classes available to take wherever and however our Members choose to move—through Peloton Bike, Bike+, Tread, Row, Guide, and App, and on any iOS and Android device and select smart TVs. Style-forward and body-inclusive, Peloton Apparel is designed to move with you towards all your goals. And with Peloton Corporate Wellness or Peloton Commercial, organizations and enterprises can also access the Peloton platform—bringing the power of interactive fitness to their teams and customers.

Innovation-driven and entertainment-led, Peloton is so much more than an exercise brand. It is a global leader at the intersection of fitness, technology, and media.

The Enterprise Data Analytics team at Peloton is looking for a passionate and strategic-minded Data Analyst to join our growing team. This person will contribute to key projects that enhance visibility into key enterprise metrics and drive action based on the resulting insights. They will partner closely with teams across the company to understand their problems and design datasets that can provide actionable insights in a scalable and sustainable way. They will communicate findings and implications for stakeholders from various functions. This person will report to the Manager of Analytics.

YOUR DAILY IMPACT AT PELOTON

• Work with members across the Marketing and Peloton for Business organizations to translate their challenges into innovative data solutions
• Architect performant, accurate, and scalable data models using dbt and LookML using DRY (don’t repeat yourself) principles
• Design self-service data products that make datasets accessible and intuitive to a broad group of data consumers
• Set up tests to ensure data quality, supervise daily job execution, and diagnose/fix issues to ensure SLAs are met with internal stakeholders
• Identify and investigate emerging trends and anomalies in key performance indicators
• Balance requests and strategic initiatives to prioritize work based on impact for the business
• Clearly articulate and communicate findings to stakeholders across functional groups to influence actions and decisions that advance the company’s strategic goals

At Peloton, we’ve invested in a modern data tech stack (Redshift, Airbyte, Airflow, dbt, Looker) and a world-class data team. If you’re passionate about using the best technology and being part of a growing team that values teamwork, proactivity, disciplined decision-making, and knowledge sharing, we’d love to hear from you.

YOU BRING TO PELOTON

• 3+ years of relevant business intelligence or analytics development experience
• Experience building Looker data models (LookML), data pipeline management technologies with dependency checking (e.g. Airflow, dbt), schema design, and dimensional data modeling
• Skilled at finding trends in the data, articulating the “so what,” and translating insights into strategic, actionable recommendations.
• Ability to anticipate follow-up questions and incorporate them into analysis to address the core problem, not just the direct question.
• An open and adaptable mindset and a strong team player (no job is too small or too large) and willing to take on additional responsibilities as necessary.
• Ability to work in a fast-paced, ever-changing environment where priorities are often shifting.
• Experience creating dashboards and self-service capabilities for stakeholders through reporting tools (Looker, Tableau, etc.)
• Understanding of SQL, columnar databases, and distributed file systems.
• Ability to optimize queries and pipelines for efficient performance.
• Experience building data transformations with dbt or equivalent software
• Experience applying statistical techniques to understand and quantify the relationships between metrics and differentiate between correlation and causation.
• Working knowledge of python, especially libraries and packages focused on data processing and analysis