Principal Product Analytics Engineer

Toast Toast · Enterprise · United States · Remote · R & D : Product : Shared

This role focuses on building the technical foundation for product analytics, including data capture, structuring, and availability for analysis. It involves designing systems for telemetry, experimentation, and AI-driven insights to understand user behavior and measure product impact. The role emphasizes creating scalable data models and ensuring data reliability to support data-driven product development and AI workflows.

What you'd actually do

  1. Lead the architecture and design of Toast’s product analytics data ecosystem, spanning product telemetry, event pipelines, analytics-ready datasets, and semantic views.
  2. Establish scalable data models that support product analytics, experimentation, executive reporting, and AI-powered insights.
  3. Design frameworks for core analytics concepts such as sessions, identity resolution, feature usage tracking, and lifecycle metrics.
  4. Develop and maintain reliable analytics layers of the product data warehouse using modern modeling frameworks.
  5. Create reusable analytics datasets, standardized metrics, and canonical models used across product teams.

Skills

Required

  • Data Engineering
  • Product Analytics
  • Data Analysis
  • Data Science
  • large scaled product data
  • web & mobile apps, Android OS software and devices
  • product analytics data infrastructure
  • schema design
  • ETL/pipelines
  • warehouses
  • datasets for AI-driven analytics
  • Amazon S3 Data Lake
  • Airflow
  • dbt
  • Snowflake
  • Hex
  • Sigma
  • Amplitude
  • Python
  • SQL
  • modeling skills
  • AI tools like Claude, Cursor, Chatgpt, MCP
  • stakeholder needs and requirements
  • data foundations for experimentation and A/B testing
  • cross-functional leadership
  • documentation and presentation

Nice to have

  • AI tools like Claude, Cursor, Chatgpt, MCP

What the JD emphasized

  • AI-driven analytics
  • AI workflows
  • AI tools