Director, Customer Success Data Engineering

📋 Description

• Own the redesign of the unified CS data model across Care, CX, Enablement, and CSS.
• Define and execute the AI data strategy for CS: pre-calc vs dynamic retrieval.
• Build and maintain a documentation layer as a first-class artifact.
• Develop a clear framework for when AI is the right tool vs traditional data.
• Lead a small team of two senior data and analytics engineers to start.

🎯 Requirements

• 10+ years in data platform, modeling, or analytics engineering; 3+ in leadership.
• AI-ready data models for retrieval vs pre-calc; documentation as infrastructure.
• Snowflake, dbt, or equivalent; semantic layer for consistent metrics.
• Treat pipelines like software: tests, schema validation, freshness checks.
• Diagnose systemic data quality issues and redesign architectures.
• Strong cross-functional communication translating data decisions for stakeholders.

🎁 Benefits

• Hybrid work model with in-person collaboration.
• Diversity, Equity, and Inclusion baked into our culture.
• Collaborative, cross-functional environment across CS and data teams.
• Opportunity to shape greenfield CS data and AI strategy.
• Growth and leadership development opportunities.