Principal Analytics Engineer - Analytics & AI

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Job : R48670

Primary

Location:

Eden Prairie, MN United States of America

Secondary Location(s) :
Chicago, IL United States of America

At C.H. Robinson, we're transforming the way data powers decisions across our global business. As a Principal Analytics Engineer - Analytics and AI, you'll play a key role in advancing our analytics strategy by designing modern, scalable business intelligence solutions that combine data, automation, and AI to deliver faster, more trusted insights.

You’ll operate at the intersection of software engineering, data architecture, business intelligence, and artificial intelligence—building enterprise‑scale analytics products that are secure, scalable, and designed for the future. You’ll serve as both a technical leader and strategic partner, translating complex business challenges into enterprise analytics products that enable self‑service reporting, intelligent automation, and AI‑powered decision support. You’ll lead the design and evolution of trusted data assets, semantic models, dashboards, and automated workflows while helping shape the future of how data is accessed, governed, and consumed across the organization.

Leveraging deep expertise in Power BI, SQL, Snowflake, data modeling, and analytics architecture, you’ll partner with cross‑functional teams to build scalable solutions that improve operational efficiency and business outcomes. You’ll also help drive adoption of emerging technologies—including Microsoft Copilot, AI‑assisted development, workflow automation, and conversational analytics—to enhance productivity and create next‑generation user experiences.

If you're passionate about combining business intelligence, data architecture, automation, and AI to solve complex business problems, this is an opportunity to make a lasting impact on one of the world's largest logistics and supply chain organizations while helping shape the future of data‑driven innovation at C.H. Robinson.

The duties and responsibilities of this position consists of, but are not limited to, the following:

• Design analytics solutions using software engineering best practices to ensure scalability, maintainability, and long‑term supportability.
• Build reusable analytics components, semantic models, and shared data services that accelerate enterprise adoption.
• Lead adoption of AI‑assisted development, automation, and engineering practices within the Analytics organization.
• Partner with software engineering and platform teams to integrate analytics into enterprise applications through APIs and event‑driven architecture.
• Extract and interpret data to answer ambiguous questions while working directly with personnel across the network.
• Determine reporting, analytics, and additional analysis needed to support initiatives and measurement.
• Proactively analyze topics, identify insights, and create recommendations supported by facts to change behaviors and drive operational improvements across the team and business.
• Clearly translate and communicate complex concepts into understandable, professional presentations.
• Consult, support, and inform leadership using data‑driven insights.
• Translate business needs into technical specifications and scalable analytical solutions.
• Analyze, design,…