Analytics Engineer
The Enterprise Data team works alongside multiple departments to help them get the most out of their data. As an Analytics Engineer, you’ll work with stakeholders to build models and serve as a subject-matter guide on the best processes surrounding analysis. Peloton is looking for a talented individual to build and maintain foundational data infrastructure crucial to gaining insights.
Your Daily Impact at Peloton
- 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 while incorporating DRY (don’t repeat yourself) principles
- Set up tests to ensure data quality, supervise daily job execution, and tackle roadblocks to ensure SLAs are met
- Understand business context and support analysts/business stakeholders in crafting and standardizing source-of-truth Looker Explores and Dashboards
- Document work, prioritize data governance, and provide team members with insight into standard processes
You Bring to Peloton
- 4-6 years of experience in an analytics engineering, data engineering, business intelligence, or technical data analytics role supporting a variety of business domains
- 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
- 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
- Plus: Knowledge of AWS ecosystem/CLI and data ingestion tools (e.g. Fivetran, Stitch)
- Serious plus: You’ve worked at a SaaS company with a hardware component (or vice versa)
Base Salary: $117,100.00 to $152,900.00