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 CS AI data strategy, balancing pre-calc vs dynamic AI retrieval.
• Build and maintain a documentation layer as a first-class artifact for reliable AI data access.
• Develop and apply a framework for when AI is the right tool versus traditional data approaches.
• Lead data integration for contact center migration and design pipelines for analytics/AI use cases.
• Lead and mentor two senior data engineers; partner with CS leaders.

🎯 Requirements

• 10+ years in data platform/analytics roles, with 3+ years in leadership.
• AI-ready data model design with retrieval vs pre-calc tradeoffs.
• Hands-on with Snowflake, dbt, or equivalent; semantic layer for metrics.
• Pipelines treated like software: tests, schema validation, freshness checks, and code reviews.
• Proven ability to diagnose data quality issues and redesign architectures.
• Strong cross-functional comms translating architecture for non-technical stakeholders.

🎁 Benefits

• Hybrid work model enabling in-person collaboration and flexibility.
• Inclusive, diverse culture baked into our success.
• Accessible hiring with accommodations for disabilities.
• Global and regional approach to locations and in-office expectations.
• Greenfield data work with lasting impact, building from the ground up.
• Growth in a lean team with room to scale and develop leadership.