Director, Customer Success Data Engineering at Toast

Toast, Inc.

Hybrid

Quick summary

Work type: Hybrid
Location: New York, NY
Salary: $217,000–$347,000 / yr
Posted: today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $200k

This role $282k

$147k most similar roles pay here $368k

This role pays more than 93% of similar roles. Most pay $170,250–$229,442 — the shaded band above. At the midpoint, this role pays about $282k versus about $200k for comparable roles.

Based on 240 similar postings.

Employer

About Toast, Inc.

Toast is a cloud-based restaurant management platform providing point-of-sale, payment processing, and operations software for the food service industry.

Toast, Inc. currently has 36 open roles on FindRole.

Listed pay typically runs $190,000–$304,000 across 35 roles with salary data.

Most-posted roles

View all roles at Toast, Inc.

At a glance

TL;DR · Director, Customer Success Data Engineering at Toast

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As the Director of Customer Success Data Engineering at Toast in New York, you will lead a small team to redesign and maintain the CS data model, ensuring it supports both traditional reporting and AI-driven insights. You’ll define how data is accessed and queried across various teams and systems, including the new contact center platform, while also developing pipelines for analytics and AI/ML use cases. Key responsibilities include leading data integration efforts, establishing robust testing and monitoring practices, and collaborating with cross-functional peers to ensure data governance standards are met. The ideal candidate has over 10 years of experience in data engineering roles, including leadership positions, and expertise with tools like Snowflake and dbt. This role requires a deep understanding of AI consumption patterns and the ability to translate complex business problems into actionable data architecture decisions.

Skills

Snowflake dbt Airflow Kafka Kinesis Python SQL CI/CD Docker Prometheus Grafana Terraform AWS Azure Git Jira Confluence PostgreSQL MongoDB Redis ELK Stack SaaS

What you'll do

Own the redesign of the unified CS data model, connecting data across multiple teams and systems.
Define and execute AI data strategy for Customer Success, balancing pre-calculation with dynamic retrieval.
Lead data integration for contact center platform migration, ensuring reliable data flow into CS data layer.
Design and optimize pipelines for analytics, reporting, and AI/ML-driven use cases in CS.
Manage and mentor a small team of senior data and analytics engineers to build high-performance capabilities.

What we're looking for

10+ years of experience in data platform, modeling, or analytics engineering roles.
At least 3 years of leadership experience managing data teams and initiatives.
Experience designing AI-friendly data models with documentation as a priority.
Hands-on expertise with modern data stack tools like Snowflake and dbt.
Proven ability to diagnose and redesign systemic data architecture issues.
Strong cross-functional communication skills for translating technical decisions.

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