Staff Analytics Engineer

Toast creates technology to help restaurants and local businesses succeed in a digital world helping business owners operate increase sales engage customers and keep employees happy.

About Toast

At Toast were building the restaurant platform that helps restaurants adapt take control and thrive. The Customer Success (CS) organization plays a pivotal role in helping customers get the most out of our products and were transforming our data capabilities to drive a new era of proactive data-informed customer engagement.

The CS Data & Analytics team is at the center of this transformation building the data infrastructure that makes proactive data-informed customer engagement possible at scale for 150000 restaurant locations.

Role Overview

Youll be a founding member of a newly chartered data engineering function within Customer Success with a direct hand in shaping the architecture tooling domain model and team culture from day one. This is a rare opportunity to build something from greenfield with visibility to VP and senior CS leadership.

As an Analytics Engineer on the Customer Success Data & Analytics team youll bridge the gap between raw data and business-ready insights. Youll build the semantic layer dbt models and analytics datasets that power reporting dashboards and AI-driven workflows across the CS organization. Reporting to the Director of Data Infrastructure & Engineering youll work closely with Data Engineers Analysts and CS operations leaders to ensure data is not just available but trusted consistent and decision-ready.

This is a hands-on role focused on data modeling metrics standardization and analytics infrastructure with a direct line to CS outcomes like customer retention agent performance and proactive customer engagement.

A day in the life (Responsibilities)

• Build and maintain dbt models that transform raw CS source data from systems like Salesforce Five9 Intercom NICE and LevelAI into clean analytics-ready datasets across CS domains including Customer 360 case management omnichannel interactions and agent performance.
• Design and own the semantic and metrics layer for CS KPIs including customer health scores CSAT case resolution rates handle time and retention signals ensuring consistent definitions across all reporting surfaces.
• Partner with CS analysts and business stakeholders to translate reporting requirements into reusable well-documented data models.
• Implement data testing validation and observability frameworks to ensure CS data assets are reliable and trustworthy at all times.
• Contribute to self-service analytics enablement by building datasets and semantic models in Snowflake and Sigma/Hex that allow CS analysts and operations leaders to answer questions independently.
• Collaborate with Data Engineers to ensure upstream pipeline outputs are modeled correctly and fit for purpose for analytics use cases.
• Establish and enforce data modeling standards naming conventions and documentation practices that scale as the team grows.
• Support AI and ML use cases by building clean structured feature datasets for customer health scoring churn prediction and agent assist models.
• Participate in code reviews design discussions and technical architecture planning to continually raise engineering standards.
• Ensure data pipelines storage and access patterns adhere to BTT data standards security policies and compliance requirements.
• Partner with BTT governance forums to align on design patterns data architecture decisions and SLA expectations.
• Maintain documentation and metadata for all data assets in accordance with established governance processes.

What youll need to thrive (Requirements)

• 5 or more years of experience in analytics engineering data engineering or a related role with a strong focus on data modeling and analytics infrastructure.
• Expert-level SQL and hands-on experience with dbt for building and maintaining data models in a cloud data warehouse environment.
• Experience with Snowflake or a comparable modern data warehouse such as BigQuery or Redshift.
• Familiarity with BI and analytics tools such as Sigma Hex Tableau or Looker.
• Strong understanding of dimensional modeling metrics layers and analytics-ready dataset design.
• Ability to translate ambiguous business requirements from non-technical CS stakeholders into clean scalable data models.
• Demonstrated ability to implement data quality testing monitoring and documentation as a standard practice.
• Demonstrated ability to communicate technical tradeoffs and data concepts clearly to non-technical stakeholders including operations and business leaders.
• Collaborative working style with experience partnering across Data Engineering Analytics and business operations teams.
• Strong problem-solving skills attention to detail and a drive to build scalable reliable systems.
  
  

What will help you stand out (Non-essential Skills/Nice to Haves)

• Experience building and optimizing data systems that operate at significant scale managing billions of records across multiple data domains and systems with the foresight to design for 5-year growth and future platform scale.
• Comfort using AI-assisted development tools such as GitHub Copilot Claude or Snowflake Cortex AI to accelerate pipeline development testing and documentation and curiosity about how GenAI can enhance data product quality.
• Experience with real-time data streaming using Kafka Kinesis or Pub/Sub.
• Exposure to data governance metadata management and observability tools.
• Background in SaaS or Customer Success analytics including usage data retention metrics and customer health.
• Experience working with CS or CX-adjacent source systems such as Salesforce Five9 Intercom or similar CCaaS/CRM platforms and familiarity with the data models and integration patterns they produce.
• Knowledge of data security privacy and compliance in cloud environments.
• Experience with CI/CD infrastructure as code or containerization such as Docker or Terraform.

AI at Toast

At Toast one of our company values is that were hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster more independently and with higher quality. We provide these tools across all disciplines from Engineering and Product to Sales and Support and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; its a core part of our culture.

Our Total Rewards Philosophy

We strive to provide competitive compensation and benefits programs that help to attract retain and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters changing needs. Learn more about our benefits at base salary range for this role is listed below. The starting salary will be determined based on skills experience and geographic addition to base salary our total rewards components include cash compensation (overtime bonus/commissions if eligible) equity and benefits. You can learn more about how we align pay with local labor markets in our Geographic Pay Zone Philosophy.