JobsGenerac

Marketing Analytics Engineer II

Generac · Waukesha, WI

Posted Sep 10, 2026 · We last checked this listing on Sep 20, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

Behavioral

Walk me through a time you built a marketing dashboard or report that executives actually used to make a decision. What was in it and why?

whether the candidate can translate raw data into something decision-makers act on, not just build a pretty chart

Give me an example of a time you had to merge messy data from several sources, like sales, operations, and consumer behavior, into one clean dataset. What went wrong and how did you fix it?

real experience with data integration pain points and troubleshooting, not just theoretical knowledge

Tell me about a time a stakeholder asked for a report that, in your judgment, wasn't going to answer their real question. What did you do?

willingness to push back constructively and translate vague business asks into the right analysis

Describe a time you had to teach or support a less experienced analyst on best practices for data handling or visualization.

mentoring ability and whether they can scale their own knowledge across a team

Tell me about a marketing KPI you helped define or redefine because the old one wasn't tracking the right thing.

business judgment and understanding of what makes a metric meaningful, not just measurable

Technical

Tell me about a marketing attribution or campaign measurement project you worked on. How did you decide which model or approach to use?

depth of hands-on experience with attribution methodology versus surface-level familiarity

How would you write a SQL query to pull weekly campaign performance across multiple channels when the data lives in separate tables with inconsistent naming conventions?

practical SQL fluency and ability to handle real-world data inconsistency

You're asked to build a predictive model to forecast which customers are likely to respond to a promotion. Walk me through your approach from data prep to deployment.

whether the candidate can actually execute end-to-end predictive modeling, not just describe algorithms

Have you worked with Databricks or a similar cloud platform for analytics? What did you build there and what were the limitations you ran into?

genuine hands-on cloud platform experience versus buzzword familiarity

What's an example of unstructured data you've had to work with, like text or open-ended survey responses, and how did you turn it into something usable?

whether they've truly handled unstructured data or only worked with clean structured datasets

Situational

Say a VP asks you to explain a drop in conversion rate that your model flagged, but they don't want to hear about regression coefficients. How do you explain it?

ability to communicate complex findings to non-technical stakeholders

If two dashboards you maintain show conflicting numbers for the same metric and a director notices before you do, what's your next move?

data governance instincts and how the candidate handles being caught off guard

You have three competing requests this week: a forecasting model due for leadership, a broken dashboard someone reported, and a new data pipeline a business partner wants designed. How do you decide what to work on first?

prioritization skills and self-management under competing deadlines

Practice this interview out loud.

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The full job description

As published by Generac.

We believe power is a promise - a shared commitment to be there for others when it matters most. For more than 65 years, we've turned big ideas into solutions that help protect homes, strengthen businesses and build a more resilient, efficient, sustainable energy future. Ready to Power a Smarter World with us? The Marketing Analytics Engineer II is responsible for executing analytics initiatives across various marketing domains including media performance measurement, marketing attribution, consumer behavior modeling, and strategic KPI reporting. The role blends the rigor of data science with the practicality of engineering and business analysis. This individual will analyze structured and unstructured data using statistical analysis, predictive modeling, and data mining techniques to develop actionable insights and recommendations. Working closely with business stakeholders and data engineering teams, this role supports the development of data infrastructure and delivers analytic solutions to improve business outcomes. Major Responsibilities Collaboration & Requirements Gathering: • Partner with data engineering and business stakeholders to define analytical requirements and design robust data pipelines and models. • Translate marketing and business needs into scalable data and reporting solutions. • Support experimentation efforts and analyze marketing campaign impact. Reporting Development: • Design, develop, and optimize dashboards and reporting frameworks for marketing analytics and KPI monitoring. • Ensure timely, accurate delivery of reports and insights to cross-functional teams and executives. Data Preparation & Integration: • Prepare and clean structured and unstructured data to ensure quality and consistency. • Merge and extract data across multiple sources (e.g., sales, operations, consumer behavior) into unified repositories to enable holistic insights. Advanced Analytics & Predictive Modeling: • Develop, deploy, and maintain statistical and predictive models using machine learning techniques. • Perform exploratory and explanatory data analysis, benchmarking, and forecasting. • Utilize cloud computing and open-source tools for scalable analytics. Performance Metrics & Process Improvement: • Define and refine marketing performance metrics aligned with business goals. • Lead initiatives to automate workflows and improve data-driven decision-making processes. User Support & Documentation: • Provide user training and documentation to facilitate self-service analytics. • Support less experienced analysts and promote best practices in data handling and visualization. Minimum Job Requirements Education: • Bachelor’s degree in Data Science, Computer Science, Statistics, Marketing Analytics, or a related field is required. Experience: • 2+ years of experience in data analytics, business intelligence, or marketing analytics. Technical Skills: • Advanced proficiency in SQL and/or Python. • Strong skills in Power BI and Excel for dashboard creation and reporting. • Familiarity with data modeling, ETL pipelines, and cloud-based platforms such as Databricks. • Ability to manipulate and analyze unstructured data. Analytical & Soft Skills: • Strong problem-solving, statistical, and modeling skills. • Ability to communicate complex analytical findings to non-technical audiences. • Highly organized, self-motivated, and able to manage multiple priorities. • Strong collaboration and stakeholder engagement capabilities. #LI-BB1 Physical Demands: While performing the duties of this job, the employee is regularly required to talk and hear; and use hands to manipulate objects or controls.  The employee is regularly required to stand and walk.  On occasion, the incumbent may be required to stoop, bend, or reach above the shoulders.  The employee must occasionally lift up to 25 pounds. Specific conditions of this job are typical of frequent and continuous computer-based work requiring periods of sitting, close vision, and the ability to adjust focus. Occasional travel. “We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, disability status, protected veteran status, or any other characteristic protected by law.”

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