Principal Analytics Engineer at Toast

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, we're 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 we're 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 ~150,000 restaurant locations. Role Overview You'll 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, you'll bridge the gap between raw data and business-ready insights. You'll 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, you'll 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 you'll 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 we're 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; it’s 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 [Upgrade to PRO to see link] The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In 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. Pay Range$138,000—$221,000 USDHow Toast Uses AI in its Hiring Process Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are made by people. Diversity, Equity, and Inclusion is Baked into our Recipe for Success At Toast, our employees are our secret ingredient—when they thrive, we thrive. The restaurant industry is one of the most diverse, and we embrace that diversity with authenticity, inclusivity, respect, and humility. By embedding these principles into our culture and design, we create equitable opportunities for all and raise the bar in delivering exceptional experiences. We Thrive Together We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the restaurant community. To learn more about how we work globally and regionally, check out: [Upgrade to PRO to see link] Apply today! Toast is committed to creating an accessible and inclusive hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact [Upgrade to PRO to see contact]. ------ For roles in the United States, it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.