Analytics Engineer

Loop•Chicago, IL

133d•$140,000 - $160,000•Onsite

About The Position

As an Analytics Engineer at Loop, you will help mature the data organization by working cross-functionally with Engineering, Product, Design, Strategy & Operations, and AI Platform teams. You will design, build, and own core infrastructure and data models that enable internal and client-facing analytics and accelerate data-driven decision-making. This is an in-person role based in Loop’s Chicago office, with an expectation of being onsite at least four days per week.

Requirements

At least 2 years of experience building analytical products, such as systems, dashboards, or models.
Strong proficiency in SQL and Python for data transformations and automation.
Hands-on experience with modern data stack tools such as Snowflake, dbt, Dagster, Airflow, or Looker.
Excellent business communication skills and ability to translate data insights into actionable business strategies.
Experience with data dashboarding and visualization tools such as Tableau, Looker, Superset, or Mode.
Ability to manage, optimize, and scale data infrastructure.

Nice To Haves

Global supply chain experience in transportation and logistics.
Previous experience setting up a data stack from scratch at a startup.
Interest or experience working with cutting-edge open-source data tools.
Ability to convert ad-hoc data requests into scalable, automated pipelines.
Experience working in the logistics domain.

Responsibilities

Design, build, and maintain Loop’s core data models and ETL processes.
Establish and govern key business metrics to ensure consistency across teams.
Ensure data accuracy and reliability and maintain strong SLAs.
Turn ad-hoc data requests into scalable, repeatable pipelines.
Manage and optimize data infrastructure for performance, cost, and compliance.
Create data-driven solutions and embedded analytics to support business and product teams.