Analytics Engineer

Analytics Engineer

Chicago

Loop is industrializing services through AI, starting with one of the world's most complex industries: the global supply chain. We're an AI-native company built to solve the systemic data problem that's held logistics back for decades. Our Logistics Data Platform turns fragmented, unstructured data into a trusted foundation that fuels automation, financial clarity, and decision intelligence at scale. Today, Loop serves >20% of the Fortune 100, manages over $30B in supply chain spend, and helps its clients save hundreds of millions of dollars each year.

Our team brings deep expertise from Uber, Google, Microsoft, Meta, Amazon, Flexport, C3 AI, VMware, Box, UPS, and C.H. Robinson and we're looking for builders who want to help shape what comes next.

About the Role

As an Analytics Engineer at Loop, you will play a pivotal role in maturing the data organization. You'll work cross-functionally across Engineering, Product, Design, Strategy & Operations, and AI Platform teams to design, build, and own the core infrastructure and data models. These systems will enable both internal and client facing analytics, accelerating data-driven decision-making throughout the company and our clients.

This is an in-person role based in one of our Chicago, SF, or New York offices, with the expectation of being onsite 4+ days per week.

What You'll Do

• Own Core Data Models and ETL Pipelines: Design, build, and maintain Loop's core data models and ETL processes.
• Define Metrics and Governance: Establish and govern key business metrics for consistency across teams.
• Maintain Data Quality and Uptime: Ensure data accuracy and reliability with strong SLAs.
• Automate Data Requests: Convert ad-hoc data requests into scalable, repeatable pipelines.
• Optimize Data Infrastructure: Manage and optimize data infrastructure for performance, cost, and compliance.
• Develop Data Products: Create data-driven solutions and embedded analytics to support business and product teams.

Qualifications

• 2+ years experience building analytical products (system, dashboard, models).
• Strong proficiency in SQL and Python for data transformations and automation.
• Hands-on experience with modern data stack tools (e.g., Snowflake, dbt, Dagster, Airflow, Looker).
• Excellent business communication skills to translate data insights into actionable business strategies.
• Experience with data dashboarding and visualization tools (e.g., Tableau, Looker, Superset, Mode).
• Ability to manage, optimize, and scale data infrastructure.

Nice to Have

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

Compensation and Benefits

The base pay range for this role is $140,000 to $160,000 annually. This range reflects the base pay that Loop reasonably expects to pay for the position at the time of hire. Actual compensation will depend on job-related factors, including experience, skills, qualifications, location, and business needs.

In addition to base salary, this role may be eligible for equity. This role is also eligible for Loop's benefits, including health, dental, and vision insurance, 401(k) match, paid time off, paid holidays, and parental leave.

Equal Opportunity

Loop is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.