Director of Data Engineering & Infrastructure, Toast

• 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

Desirable

• 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
• Define and execute the data infrastructure vision and roadmap for Customer Success in alignment with enterprise data strategies and Toast’s 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
• 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 team’s best practices
• Partner with the centralized BTT data architecture team to ensure platform integrity, metadata management, and observability
• 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
• 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
• 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