FIND_THE_RIGHTJOB.
Naperville, United States
Overview
The Marketing Data Analyst will work at the intersection of data engineering, analytics, and digital marketing: connecting systems, analyzing engagement and ad performance, and helping forecast customer growth. This position will work will directly to support the sales and marketing teams by ensuring the right data flows into the right places at the right time — from ad platforms to CRM reporting.
Reports To: Director of Digital Strategy
Department: Digital Strategy
Job Status: Exempt
Responsibilities:
Support the collection, orchestration, and activation of marketing and advertising data across platforms (CRM, automation, Google/Meta/LinkedIn Ads, analytics tools).
Build and maintain pipelines and reverse ETL processes that keep dashboards, campaigns, and CRM systems up to date.
Develop forecasting models and reports that connect engagement and advertising spend to revenue growth.
Produce clear ad performance reports that highlight ROI, efficiency, and optimization opportunities.
Apply statistical and analytical methods to uncover customer journey patterns, lead quality drivers, and campaign impact.
Create dashboards and visualizations to make insights accessible for marketing, sales, and leadership.
Collaborate with cross-functional teams to ensure data is powering campaigns effectively.
Experiment with AI tools to speed up workflows and enhance analytics
Bachelor’s or Master’s degree in a data-related field (Data Science, Computer Science, Marketing Analytics, Statistics, or similar). – required
1–2 years of experience (professional, internship, or research) working with data in a marketing, advertising, or analytics context. – required
Proficiency with Python, SQL, or similar languages for data manipulation and analysis. – required
Familiarity with BI/visualization tools (e.g., Tableau, Power BI, Looker, etc.). – required
Strong communication skills and ability to translate data into business recommendations. – required
Exposure to digital advertising platforms (Google Ads, Meta Ads, LinkedIn Ads, etc.) and their reporting ecosystems.
Experience with marketing technology stacks (CRM, automation, customer data platforms).
Experience with data orchestration or reverse ETL tools.
Coursework or projects in forecasting, marketing analytics, or campaign optimization.
Examples of how you’ve used AI tools to support analytics or marketing workflows
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