Red Hat

Senior Marketing Data Analyst

Red Hat

full-time

Posted on:

Origin:  • 🇺🇸 United States • North Carolina

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Salary

💰 $105,373 - $152,770 per year

Job Level

Senior

Tech Stack

Amazon RedshiftCloudKubernetesLinuxOpen SourcePythonSFDCSQLTableauVBA

About the role

  • Analyze success of marketing campaigns using Adobe Analytics, Tableau, SalesForce, Databricks, and RedShift.
  • Mine, analyze and model data using SQL, Python, or R in Databricks and RedShift.
  • Build tables, graphs, charts, and dashboards using Tableau desktop.
  • Translate data findings into visualizations with a corresponding story to share with stakeholders.
  • Present data findings via slide decks to Red Hat’s executive teams and on company-wide calls.
  • Collaborate with data science teams to build predictive and prescriptive data models.
  • Act as a subject matter expert on how Red Hat runs as a business and use that context when analyzing data.
  • Drive action from data findings to help increase revenue for future marketing campaigns.
  • Evaluate existing business processes and streamline current reporting on campaign performance.

Requirements

  • Bachelor's degree (U.S. or foreign equivalent) in Business Administration, Business Analytics, Statistics or related field and five (5) years of experience OR Master’s degree (U.S. or foreign equivalent) and three (3) years of experience.
  • Minimum three (3) years of experience with Adobe Analytics, Google Analytics, Eloqua, SalesForce.com, Tableau, or similar systems and tools.
  • Experience mining and analyzing data, providing actionable insights and serving as a consultant to internal stakeholders.
  • Experience presenting analytics simply and actionably, including analytical reports to monitor campaign performance.
  • Experience with business intelligence, database mining, statistical analysis, and data science tools.
  • Experience managing large data sets and performing analysis using Macros, VBA, Google Scripts, R, Python, or SQL.
  • Experience presenting data analyses with global stakeholders and leadership.
  • Ability to translate data into visualizations and craft narratives for stakeholders; collaborate with data science teams.