Principal Product Analytics Engineer

Toast creates technology to help restaurants and local businesses succeed in a digital world. They are seeking a Principal Product Analytics Engineer to define and build the technical foundation of their product analytics ecosystem, ensuring product data is reliable, scalable, and supports data-driven product development.

Responsibilities:

• You will design systems and frameworks that power product telemetry, experimentation, analytics datasets, and AI-driven insights to enable product teams to understand user behavior and measure product impact
• Working closely with Product, Engineering, Design, Data Platform, and Data Infrastructure teams, you will ensure product data is reliable, scalable, and built to support data-driven product development
• You will use AI to deliver and improve the speed of insights into the product development lifecycle
• Lead the architecture and design of Toast’s product analytics data ecosystem, spanning product telemetry, event pipelines, analytics-ready datasets, and semantic views
• Establish scalable data models that support product analytics, experimentation, executive reporting, and AI-powered insights
• Design frameworks for core analytics concepts such as sessions, identity resolution, feature usage tracking, and lifecycle metrics
• Develop and maintain reliable analytics layers of the product data warehouse using modern modeling frameworks
• Create reusable analytics datasets, standardized metrics, and canonical models used across product teams
• Implement automated data validation, monitoring, and quality controls to ensure reliable product data
• Partner with engineering teams to define and enforce product telemetry and instrumentation best practices
• Establish governance processes that ensure consistent metric definitions and high-quality data across domains
• Partner with analysts, data scientists and product managers to ensure the data foundation supports experimentation, dashboards, analytical studies, and AI workflows
• Serve as the technical authority on product data architecture, reliability and governance
• Mentor team members to help elevate the organization’s ability to leverage product data effectively

Requirements:

• Bachelor's degree in Computer Science, Information Systems, or a related field with a minimum of 12 years of experience in Data Engineering, Product Analytics, Data Analysis, Data Science or related field; or a Master's degree with 8 years of related experience; or a PhD with 5 years of experience; or equivalent experience
• Experience working with large scaled product data from source to warehouse, specifically with web & mobile apps, Android OS software and devices
• Deep experience designing product analytics data infrastructure including schema design, ETL/pipelines, warehouses, and designing datasets for AI-driven analytics
• Extensive hands-on experience with Amazon S3 Data Lake, Airflow, dbt, Snowflake, Hex, Sigma, Amplitude, Python or similar tools
• Expert level SQL and modeling skills, and experience with AI tools like Claude, Cursor, Chatgpt, MCP
• Proven ability to translate stakeholder needs and requirements into deployed scalable data architecture
• Experience supporting data foundations for experimentation and A/B testing measurement frameworks
• Strong cross-functional leadership with experience driving alignment across Product, Engineering, and Data teams
• Excellent communication skills, demonstrated through documentation and presentation to stakeholders and senior leadership
• A self-starter mindset, excited to build something from scratch and evolve it over time