Job Description
ABOUT THE ROLE
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
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