Analytics Engineer

The Analytics Engineer will help pioneer the next generation of analytics, automation, and data-driven decision making at the Denver Broncos. This role will develop and scale solutions that improve revenue generation, fan engagement, operational efficiency, and organizational decision making through a combination of analytics engineering, predictive modeling, and AI-enabled workflows., The Denver Broncos are one of the most popular franchises in all of sports. Whether judged by the measure of wins and championships, attendance, national television exposure or by the Broncos’ reputation locally and throughout the NFL, there are few parallels in the world of professional sports. We are dedicated to being the best team to cheer for, play for, and work for across all of sports. We are looking for employees who are passionate about what they do, have fun doing it, and proud to represent the Denver Broncos Football Club and Empower Field at Mile High.

JOB SUMMARY: The Analytics Engineer will help pioneer the next generation of analytics, automation, and data-driven decision making at the Denver Broncos. This role will develop and scale solutions that improve revenue generation, fan engagement, operational efficiency, and organizational decision making through a combination of analytics engineering, predictive modeling, and AI-enabled workflows.

This highly visible role will partner with stakeholders across Ticketing, Marketing, Partnerships, Operations, and Leadership to build trusted data products, predictive insights, and intelligent automations that transform how the organization interacts with data., Analytics Engineering & Business Intelligence - Build trusted data products that power business decisions

• Design, develop, and maintain analytics-ready datasets, semantic models, and reusable business logic that support dashboards, reporting, machine learning models, and AI-enabled workflows
• Build and maintain ETL pipelines and data integration processes that reliably ingest, transform, and load data into the enterprise data warehouse
• Partner with analysts, engineers, and business stakeholders to create scalable reporting solutions that improve visibility into ticketing, marketing, sponsorship, ticketing and operational performance
• Deliver actionable insights by gathering requirements, developing dashboards and visualizations, and supporting ad hoc analytical requests using best practices in data integrity, validation, analysis, and documentation
• Develop attribution and measurement frameworks that help quantify the impact of fan engagement, marketing communications, and lifecycle campaigns
• Develop lead scoring and prospecting solutions that support premium, sponsorship, and future stadium sales efforts
• Develop consumer insights solutions that uncover fan behaviors and trends to inform business strategy and growth initiatives
• Serve as a trusted analytics partner to stakeholders by translating business needs into scalable and measurable data solutions

Data Science & Predictive Analytics - Develop models that improve business outcomes

• Develop, maintain, and embed predictive models into solutions that support pricing, demand forecasting, fan engagement, and customer behavior use cases
• Enhance and manage existing fan segmentation, propensity, and predictive scoring models that support personalized marketing and engagement strategies
• Partner with business stakeholders to identify opportunities where predictive analytics can improve revenue generation, customer engagement, and operational effectiveness
• Monitor, evaluate, and refine models to ensure performance, accuracy, and alignment with business goals

AI Enablement & Automation - Apply AI tools to accelerate business processes and decision making

• Build and maintain trusted data resources that make it easy for employees, analysts, and AI tools to securely access consistent business information and insights.
• Help establish and maintain guidelines that ensure AI solutions are accurate, secure, reliable, and aligned with business needs and company policies.
• Leverage emerging analytics and agentic capabilities to transform data into proactive, contextual insights that identify opportunities and deliver timely information to stakeholders

• Bachelor’s or Master’s in a quantitative field (Computer Science, Statistics, Engineering, Data Science)
• 3-4 years of professional experience in analytics engineering, advanced analytics, data science, or related fields
• 1+ years of professional experience deploying products built on predictive modeling and machine learning (MLOps)
• Experience developing lead scoring models, prospecting strategies, and sales intelligence solutions that support customer acquisition and revenue growth
• Experience using consumer research, segmentation, and behavioral analytics to generate actionable business insights
• Expertise in SQL and Python
• Experience with Snowflake, dbt, and modern analytics engineering practices
• Experience with agentic workflows, MCP, RAG, or LLM-powered applications
• Experience building dashboards and reporting solutions using Power BI or Tableau
• Experience with data modeling, ETL development, and data warehousing
• Excellent communication and storytelling skills, capable of translating complex technical concepts into intuitive, impactful insights and driving adoption of ML and AI-driven solutions, * Experience supporting ticketing, marketing, sponsorship, or fan engagement analytics
• Experience with AI-enabled workflows, Copilot Studio, Claude, Cortex, or similar platforms
• Familiarity with SDLC, CI/CD, source control, and deployment practices

In accordance with the Colorado Equal Pay for Equal Work Act, the salary range for this role is $105,000 - $115,000.