Data Marketing Analyst

About the job

About Monster Energy Forget about blending in. That's not our style. We're the risk takers, the trailblazers, the game-changers. We're not perfect and we don't pretend to be. We're raw, unfiltered, and a bit unconventional. Our drive is just like our athletes, unrivaled. The power is in your hands to define what success looks like and where you want to take your career. It's not just about what we do, but about who we become on along the way. We are much more than a brand here. We are a way of life, a mindset. Join us.

A Day In The Life As the Sr Marketing Data Analyst, you’ll be the analytical powerhouse behind Monster Energy brand and digital marketing strategies turning complex data into meaningful insights, forecasts, and recommendations that directly influence business growth. You’ll design and manage modern data solutions in Microsoft Fabric and OneLake, build automated pipelines using SQL, Python, and Medallion architecture, and create dynamic Power BI dashboards that fuel smarter decisions across the organization. Partnering closely with IT, brand teams, and digital marketing channels, you’ll ensure data integrity, security, and seamless reporting while uncovering trends that optimize campaign performance and strengthen brand health. You’ll also develop predictive models, enhance our star‑schema architecture, and document scalable frameworks that elevate how we measure, automate, and accelerate marketing impact.

The Impact You'll Make

• Collect, analyze, create, and interpret complex data sets to identify trends, patterns, and insights that drive digital and brand marketing decisions in MS Fabric using Power BI.
• Maintain One Lake data, including data ingestion from new data sources and monitor, implement automated data pipeline monitoring and validation routines to ensure ongoing data integrity, accuracy and reliability.
• Create accurate forecasts using statistical methods and historical data to support brand and digital marketing planning.
• Leverage advanced analytical and statistical methods to predict future trends collecting and analyzing large amounts of internal and external data utilizing statistical algorithms.
• Create data models that help measure performance, identify gaps, provides insights into marketing campaigns based on different objectives and overall business reviews at brand level.
• Utilize advanced planning systems and tools to support data-driven decision-making and maintain data integrity.
• Make data-driven decisions with greater confidence, minimizing risks and maximizing opportunities for digital marketing channels and brand health.
• Generate and present detailed reports on marketing, highlighting key metrics and areas for improvement.
• Work closely with cross-functional teams, including different brands, digital marketing channels and shopper marketing to ensure cohesive and accurate data reporting for all our stakeholders.
• Design, develop, and maintain advanced Power BI dashboards by integrating and modeling data from multiple digital marketing channels using SQL queries and Python scripts for data extraction, transformation, and automation using the Medallion architecture in MS Fabric.
• Enhance star schema architectures to optimize performance and scalability, implement DAX measures for dynamic KPI.
• Implement new ways to optimize performance and automate processes, ETLs and predictive analytics.

Who You Are

• Bachelor's Degree preferred in the field of Data Analytics, Marketing, Statistics, Economics, or related field of study
• Proficient in Microsoft Office suite, SQL, Python, DAX, Power BI,
• Certifications & Licenses: Data Modeling, MS Fabric , Power BI desired
• 5+ years of experience in data modeling, data analysis, marketing analysis
• 5+ years of experience in forecasting or predictive analytics
• Excellent verbal and written communication skills with strong business acumen, deductive reasoning, and problem solving skills

Monster Energy provides a competitive total compensation; this position has an annual estimated salary of $107,250 - $143,000. The actual pay may vary depending on your skills, qualifications, experience, and work location.