About the role

Role Overview

Analytics Engineer at Loop, bridging raw data and production analytics outputs—dbt models, dashboards, data products, and merchant outcomes. You’ll build and maintain the analytics foundation for internal self-serve reporting as well as Loop Intelligence.

What You’ll Do

Design, develop, and maintain production-quality dbt models with strong focus on performance, readability, and maintainability.
Translate business requirements into clean, well-documented data models, including ownership of code reviews and semantic/metrics layers.
Collaborate with Data Engineering on upstream ingestion and architecture, including Fivetran and Streamkap connectors; apply practical knowledge of Snowflake performance and warehouse costs.
Support a dbt contributor community beyond the core analytics team—keep contributors unblocked and help them grow.
Contribute to Loop Intelligence measurement, including merchant outcome measurement and shopper-level cohort analyses.
Apply data operations fundamentals: GitLab, CI/CD, automated testing, and documentation for discoverability and usability.
Actively use AI tools in your workflow and help define shared team norms.

Your Experience

3+ years hands-on experience as an analytics engineer, data engineer, or equivalent.
2+ years working with dbt in production (models, sources, tests, documentation).
Strong SQL and meaningful data warehouse design experience (Snowflake preferred).
Familiarity with data ops practices: Git workflows, CI/CD, and automated testing for data.
Exposure to data engineering concepts: ETL/ELT, connector tooling (Fivetran/Streamkap or similar), and warehouse optimization.
Python experience for transformation/automation (nice to have).
Business acumen in at least one area: Product, GTM, Finance, Marketing, or Customer Experience.

How You Work

Self-managing: knows when to ask for input vs. make decisions.
Clear communicator: can explain modeling decisions to both engineers and non-technical analysts.
Pragmatic judgment about when to keep it simple, do it the right way, and when to raise flags.

About Loop

Loop is a post-purchase commerce company focused on returns and exchanges at scale. It uses data and analytics to power merchant-facing insights and supports machine learning via its Loop Intelligence layer. The company builds a data stack that serves internal analytics and downstream decision-making.