Senior Analytics Engineer

Salary

Base Salary Range: $154,100—$200,400 USD

The Enterprise Data team at Peloton works with many teams to get the most out of their data. As an Analytics Engineer you’ll work with stakeholders to build models the right way and serve as a thought leader on standard methodologies around analysis. Peloton is looking for a versatile individual to join the team to build and maintain foundational data infrastructure crucial to gaining insights.

Your Daily Impact at Peloton

This hire will be instrumental in crafting the team’s technical direction and growth. We’re looking for someone who can:

Architect performant, accurate, and scalable dimensional data models using dbt and LookML using DRY (don’t repeat yourself) principles
Set up tests to ensure data quality, supervise daily job execution, and diagnose/fix issues to ensure SLAs are met with internal stakeholders
Troubleshoot, diagnose, and resolve issues with data pipelines urgently and thoroughly
Understand business context and support analysts/business stakeholders in crafting and standardizing source-of-truth Looker Explores and Dashboards
Detail your designs, prioritize data governance, and promote best practices
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 out there 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

5-7 years experience in an analytics engineering, data engineering, business intelligence, or technical data analytics role supporting a variety of business domains (Serious plus: You’ve worked with subscription and/or ecommerce based business models)
Demonstrated experience helping teams streamline and scale with improvements to technical design, code review, and analytics architecture
Expertise in SQL and ETL optimization techniques, especially within cloud-based data warehouses like Redshift, as well as use of OSX command line and version control software. (Plus: Knowledge of AWS ecosystem/CLI and data ingestion tools [e.g. Fivetran, Stitch])
Experience building Looker data models (LookML), data pipeline management technologies with dependency checking (e.g. Airflow, dbt), schema design, and dimensional data modeling
Ability to leverage tools, business intuition, and attention to detail for data validation and QA
Excellent interpersonal skills, particularly when explaining technical or sophisticated matters to less technical co-workers
Ability to document design and technical specifications in a clear and concise way.

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