Senior Manager Data Engineering & Analytics

Cherry Technologies, Inc.

1d•Remote

About The Position

We're seeking a Senior Manager of Data & Analytics Engineering to own how data moves through Cherry and how the entire company leverages it — end to end, from ingestion and warehouse architecture, through governance and access control, to the analytics engineering layer that powers self-serve analytics and decision-making across the business. You'll build and lead a team spanning both Data Engineering and Analytics Engineering, including senior individual contributors who will help you execute as the team scales. You’ll start with a core team of 2-3 engineers, and one of your immediate mandates will be to rapidly scale this team to 6-8 engineers. One of Cherry’s values is “Seek Truth Through Facts” and your primary goal is to enable data democratization that is efficient, secure and scalable. To do so, you’ll ensure that a broad range of internal stakeholders — from operational reps to executive leadership and technical data science teams — are served by the right tooling, data access, and governance model.

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
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

Nice To Haves

Background in a regulated industry (e.g., Fintech, Healthcare, Insurtech) navigating strict compliance and governance requirements is strongly preferred

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