Senior Manager, Data & Analytics Engineering

Cherry is a fast-growing FinTech company offering an inclusive buy-now-pay-later solution for medical practices. The Senior Manager of Data & Analytics Engineering will lead Data Engineering and Analytics Engineering teams, own the end-to-end data platform and governance strategy, and enable secure, scalable self-service analytics across the business.

Responsibilities:

• Build and lead a team of Analytics Engineers and Data Engineers, setting technical standards across both disciplines
• Drive rapid team scaling to expand the org to 6-8 engineers within a year, establishing clear career ladders as scope expands
• Cultivate a culture of engineering rigor, code review, automated testing, and continuous delivery
• Own the architecture and strategy for data ingestion, warehouse modeling, and the analytics engineering layer (dbt, semantic layer, marts)
• Design and enforce data governance and security frameworks: role-based access control (RBAC), PII/PHI handling, masking, and tokenization in a regulated environment
• Stay technically close enough to conduct code/architecture reviews, unblock technical bottlenecks, and step in personally on critical platform issues
• Ensure every internal stakeholder group gets the right tooling and access model for their specific needs, from operational reps and executive leadership to technical power users in Finance, Credit Risk, and Practice Risk
• Serve as the de facto product manager for data-related production systems and core infrastructure, translating requirements from internal partners into a unified, actionable roadmap
• Define frameworks governing how decentralized internal applications and rapidly prototyped tools are built on Cherry's data surfaces, keeping self-service scalable and reliable

Requirements:

• 7+ years in data engineering and/or analytics engineering, including direct people management experience
• Demonstrated ability to attract, hire, and scale engineering talent quickly while maintaining a high technical bar
• Proven track record owning end-to-end data platform architecture from ingestion through to consumption layers
• Experience operating as a product owner/liaison for technical platform tools, balancing business feature requests with technical debt and reliability
• Background in a regulated industry (e.g., Fintech, Healthcare, Insurtech) navigating strict compliance and governance requirements is strongly preferred
• Deep expertise in cloud data warehouses (e.g., Snowflake), orchestration tools (e.g., Airflow), and ingestion tooling (e.g., Fivetran)
• Mastery of dbt and core analytics engineering practices — data modeling, semantic layer design, testing, and documentation best practices
• Practical experience designing role-based access control (RBAC) frameworks, PII/PHI tokenization, masking, and automated access control systems
• Experience coaching across distinct technical role types, and building out senior/lead layers as a team scales
• Able to represent technical tradeoffs and governance requirements clearly to both engineering peers and non-technical executive stakeholders
• Strong prioritization instincts when governance work, platform reliability, and business-facing feature requests compete for the same roadmap slot