Publisher Intelligence Analyst, Global Partnerships

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 2 years of experience in Business Intelligence or Data Analytics.
  
• 2 years of experience in SQL and Data Visualization (e.g., Looker, Tableau, Power BI, Qlik, or similar technologies).
  

Preferred qualifications:

• Experience with data warehousing or data modeling concepts.
  
• Experience with big data technologies such as Hadoop, Spark, Python or R.
• Experience with translating business requirements to BI solutions.
  
• Experience explaining technical analysis to stakeholders.

About the job

As a part of the Publisher Intelligence team, you will enable Sellside Monetization leadership in the Americas to analyze past and future performance, draw actionable insights and make strategic decisions, while supporting publishing partners in growing their businesses through Google's ad products by developing reporting systems, uncovering new opportunities and driving user and advertiser engagement.

The US base salary range for this full-time position is $96,000-$138,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Consult with users or decision makers to identify data sources, required data elements or data validation standards, with some advice.
• Design business intelligence solutions and infrastructure to support data gathering, storage and retrieval, following local best practices and with recommendations.
• Develop data models to support the visualization and interpretation of data, with some guidance.
• Create reports, queries and dashboards that consolidate data from multiple sources and implement specific features and components with minimal supervision.
• Perform data analyses using relevant tools and custom or existing data models, collaborating with clients to understand their needs and clarify requirements with limited supervision.