Business Intelligence Analyst / Data Analyst (SQL)

Waymo's Data Science team is an important part of our mission to develop safe and reliable autonomous driving technology. We use data analysis and leverage statistical expertise to evaluate and improve the Waymo Driver, focusing on areas like reliability, driving quality, and safety. Our work ensures that data-driven insights inform key aspects of Waymo's development process.  As a Business Intelligence Analyst, you will help build the data infrastructure behind reporting and analytics for some core pillars supported by the Waymo Data Science team.

• As a Data Analyst, you will leverage advanced SQL and Business Intelligence tools to build state-of-the-art reporting infrastructure (data pipelines, dashboards) to ensure decision making within one of:
  • Waymo Driving Quality
  • Waymo Safety
  • Waymo Reliability
• Write high quality data pipelines with clear definitions to ensure consistency of metrics across the company
• Design, define, and govern key performance indicators (KPIs) and core metrics
• Work with Data Science, Engineering, Operations, Product, and Regulatory teams to allow accurate reporting to several audiences
• Prepare content and communicate to Waymo leadership
• Run deep analyses into data trends observed to drive partner team goals

• 4+ years of experience in a Data Analyst, Business Intelligence Analyst, or similar quantitative role within a tech-forward environment.
• Advanced SQL proficiency – you are an expert at writing high-performance queries, including window functions, UDFs, and complex joins to manipulate large-scale datasets.
• Data Engineering mindset – experience managing and querying extremely large datasets (BigQuery, Redshift, or similar) and building scalable data pipelines.

• Data Visualization & Storytelling – a proven track record of building intuitive, "executive-ready" dashboards in modern BI tools (e.g., Tableau, Looker, or Data Studio).
• Infrastructure Management – expertise in building and maintaining data infrastructure for large organizations, ensuring a clean separation between development and production environments.
• Stakeholder Influence – the ability to translate complex data trends into actionable insights for Engineering, Product, and Leadership teams.
• Proactive Problem Solving – demonstrates the initiative and foresight to identify business needs before they become critical bottlenecks.