Senior Analytics Engineer

Key Skills

Python Programming, Regression Analysis, ETL/ELT technologies, Looker, Tableau, R Programming, Clustering, Data Modelling, Data pipelines, Text segmentation

Job Description

The Data Science team at Peloton works with many teams to get the most out of their data. As a Senior Analytics Engineer you’ll work with partners to build models the right way and serve as an inspiring leader on best practices around analysis. Peloton is looking for a talented individual to join the team to build and maintain foundational data infrastructure essential to gaining insights.

YOUR DAILY IMPACT AT PELOTON

• This hire will be instrumental in shaping the team’s technical direction and growth. We’re looking for someone who can:
• Build and maintain ETL pipelines from third party sources (knowing the difference between ELT and ETL, and when each is appropriate)
• Architect performant, accurate, and scalable data models using dbt and LookML using DRY (don’t repeat yourself) principles
• Set up tests to ensure data quality, monitor daily job execution, and diagnose/fix issues to ensure SLAs are met with internal partners
• Understand business context and support analysts/business partners in creating and standardizing source-of-truth Looker Explores and Dashboards
• Document work, prioritize data governance, and evangelize best practices

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

YOU BRING TO PELOTON

• 4-6 years experience in an analytics engineering, data engineering, business intelligence, or technical data analytics role supporting go-to-market organizations.
• 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 (git). Plus: Knowledge of AWS ecosystem/CLI and data ingestion tools (e.g. Fivetran, Stitch)
• Experience with 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 complex matters to less technical co-workers