The opportunity
This role is the architect and owner of the Customer Success data model at Toast. It is critical to our mission of building a data-driven culture across Customer Success, one where data is transparent, accessible, and trusted by the teams who depend on it.
What you'll do
Own the redesign of the unified Customer Success data model, connecting data: across Care, CX, Enablement, and CSS teams and source systems including Salesforce and the contact center platform.
Define and execute the AI data strategy for Customer Success: specifically, how AI accesses, queries, and interacts with the data model. This means making active architectural decisions about when to pre-calculate and structure data versus when to allow dynamic AI retrieval, with predictability and consistency of outputs as the governing constraint.
Build and maintain a documentation layer that functions as a first-class: artifact. Reliable AI data access depends on well-structured, accurate documentation, and this person will treat it that way.
Lead the data integration for the contact center platform migration, ensuring: clean, well-modeled contact data flows into the Customer Success data layer from day one.
Design and optimize pipelines for analytics, reporting, and AI/ML-driven use cases.
Establish testing, monitoring, and alerting as standard practice across: Customer Success pipelines: freshness checks, completeness validation, anomaly detection. Stakeholders should never be the first to know something is broken.
What they're looking for
- Manage and technically mentor two senior data and analytics engineers,: providing clear direction and building a high-performance team from the ground up.
- Serve as the primary data architecture partner for Customer Success analytics: and operations leaders, translating business problems into data model and tooling decisions.
- Participate in cross-functional conversations with Finance and business: technology partners on KPI definitions, data lineage, and governance standards, in close coordination with Customer Success senior leadership.
- Ensure Customer Success data is accurate, accessible, and trusted by the: teams who depend on it, from strategic OKRs down to operational dashboards.
