Marketing Analyst, Google Workspace
@ Google

Sunnyvale, CA
$140,000
On Site
Full Time
Posted 21 days ago

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Job Details

About the Role

The Marketing Analyst, Google Workspace at Google will drive measurement, analysis, and testing initiatives supporting global and regional marketing programs. You will analyze large data sets, perform statistical analyses, and generate insights to enhance process efficiency and campaign impact.

Key Responsibilities

  • Develop and deliver regular reports to marketing leadership.
  • Conduct root cause analysis on data trends for initiatives.
  • Collaborate with regional teams to optimize marketing strategies.
  • Explore marketing data to uncover trends and growth opportunities.
  • Develop dashboards and analysis tools leveraging AI.

Qualifications

Minimum qualifications include a bachelor’s degree in research or quantitative field, 3 years experience in research design and marketing analytics, and experience in working with research agencies. Preferred qualifications include 2 years of additional marketing analytics experience, strong data analysis, data modeling skills, SQL, and the ability to create presentations for executive stakeholders.

Additional Information

The base salary range for this full-time role is $114,000-$163,000 plus bonus, equity, and benefits. Google's policy ensures equal opportunity employment and considers qualified applicants with arrest or conviction records in accordance with local labor laws.

Key Skills/Competency

  • Marketing Analytics
  • Data Analysis
  • Statistical Analysis
  • SQL
  • Dashboarding
  • AI
  • Research
  • Reporting
  • Business Insights
  • Collaboration

How to Get Hired at Google

🎯 Tips for Getting Hired

  • Customize your resume: Tailor skills and experience to Google Workspace requirements.
  • Research Google: Understand their culture, mission, and latest projects.
  • Prepare for data challenges: Brush up on SQL, analytics and AI tools.
  • Showcase results: Highlight achievements in marketing analysis.

📝 Interview Preparation Advice

Technical Preparation

Review SQL fundamentals.
Practice statistical analysis techniques.
Enhance AI dashboard skills.
Study data modeling concepts.

Behavioral Questions

Describe past campaign challenges.
Explain teamwork in data projects.
Discuss handling tight deadlines.
Share experience presenting findings.

Frequently Asked Questions