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.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data engineeringproduct analyticsdata analysisdata scienceschema designETLdata warehousingdata modelingSQLAI-driven analytics

Soft Skills

cross-functional leadershipcommunicationstakeholder managementmentoringself-starter mindset