Director, Data Engineering & Infrastructure (Customer Success)

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.

Role Overview

The Director of Data Infrastructure & Engineering in Customer Success will serve as the technical anchor for the Customer Success Data & Analytics organization leading the strategy architecture and execution of all data infrastructure initiatives across CS.

This leader will design and oversee the unified CS data model ensuring consistent reliable and high-quality data across Care Customer Success & Services (CSS) Enablement and Customer Experience (CX) analytics domains. Partnering closely with Finance and Business Technology & Transformation (BTT) the Director will ensure that Customer Success data is accurate governed and available to drive decisions at every level; from strategic OKRs to real-time operational insights.

The role will manage and mentor a small team of data and analytics engineers (and eventually data scientists) building scalable data pipelines infrastructure and analytics tooling to power a more data-driven CS organization.

What Youll Do

Leadership & Strategy

• Define and execute the data infrastructure vision and roadmap for Customer Success in alignment with enterprise data strategies and Toasts technical standards.
• Serve as a key bridge between CS BTT and Finance to ensure data alignment quality and accessibility across business domains.
• Represent CS in enterprise governance forums and data councils ensuring adherence to security architecture and compliance standards.
• Build and mentor a high-performing data engineering and (future) data science team that balances innovation with discipline and governance.
• Collaborate with analytics and operations leaders to translate business goals into data architecture tooling and workflow priorities.
  
  

Data Architecture & Platform Development

• Own the design and implementation of the unified CS data model connecting data across CS teams (Care CX Enablement CSS) and systems (Salesforce Medallia etc.).
• Lead the development and optimization of data pipelines for analytics reporting and AI/ML-driven insights and tooling.
• Drive the evolution of the CS data infrastructure to follow best in class practices and technologies in alignment with the centralized data teams best practices
• Partner with the centralized BTT data architecture team to ensure platform integrity metadata management and observability.
  
  

Data Governance & Collaboration

• Maintain transparency and rigor in KPI definitions and data lineage across CS and enterprise systems.
• Establish processes for data quality monitoring schema management and SLAs for data delivery.
• Contribute to and uphold a shared KPI dictionary data lineage map and self-service analytics framework.
• Ensure ongoing compliance with data security privacy and governance requirements.
  
  

Innovation & Enablement

• Enable data-driven decision-making across CS by building infrastructure that supports self-service analytics and operational automation.
• Collaborate with analytics and data science pods to enable predictive insights (e.g. contact reduction customer pain propensity satisfaction scoring).
• Lead innovation through AI-driven analytical methods including classification NLP and propensity modeling.
• Identify and implement emerging technologies that improve data accuracy and usability.
• Partner with CS teams to evolve real-time triggers and proactive customer engagement frameworks & tooling.
  
  

What Were Looking For

Required Qualifications

• 10 years of experience in data engineering data platform architecture or data infrastructure with at least 3 years in a leadership role.
• Proven track record in operating in cloud-based data ecosystems in complex matrixed environments.
• Demonstrated business acumen with a bias toward iterative delivery measurable impact and value creation.
• Strong expertise with modern data platforms (e.g. Snowflake BigQuery Redshift Databricks Delta Lake) and orchestration frameworks (e.g. Airflow dbt).
• Hands-on experience with programming and data languages (SQL Python Scala or Java).
• Demonstrated ability to align technical strategies with business outcomes and lead cross-functional stakeholder collaboration.
• Experience managing and mentoring engineering teams with a focus on performance reliability and scalability.
• Excellent communication and influencing skills particularly across business and technical stakeholders.
  
  

Preferred Qualifications

• Experience working in Customer Success SaaS or customer-facing operational analytics environments.
• Familiarity with data science workflows model deployment and machine learning infrastructure.
• Expertise in real-time data streaming (Kafka Kinesis or Pub/Sub).
• Experience building data governance frameworks and integrating with enterprise data management functions.
• Strong understanding of financial data alignment especially in collaboration with FP&A or Finance teams.
  
  

Success in This Role

• CS data is accurate accessible and aligned with Finance and BTT standards.
• Unified CS data model enables faster more confident insights and decision-making.
• Time-to-insight for key metrics and dashboards improves quarter over quarter.
• High-performing autonomous data engineering team delivering reliable pipelines and proactive solutions.
• Strong partnership and governance with Finance and BTT operating as a federated data organization.