Senior Manager, Data & Analytics Engineering

With Cherry, Inc

$135K — $160K *
US-AnywhereRemote in United States
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years in data and/or analytics engineering with proven management experience
  • Demonstrated ability to attract and scale technical talent effectively
  • Proven experience in managing end-to-end data platform architecture
  • Experience as product owner balancing business needs with technical reliability
  • Background in regulated industries is highly preferred
  • Deep expertise in cloud data warehouses and orchestration tools
  • Experience in governance practices, particularly RBAC and data security

Responsibilities

  • Build and lead a team of Analytics and Data Engineers to set technical standards
  • Rapidly scale the engineering team to 6-8 members, defining career paths
  • Cultivate a culture emphasizing engineering rigor and continuous delivery
  • Own data ingestion architecture, warehouse modeling, and analytics strategy
  • Design and enforce data governance and security frameworks
  • Conduct technical reviews and unblock bottlenecks in platform issues
  • Serve as the product manager for data systems translating partner needs into actionable roadmaps

Benefits

  • Competitive base salary plus bonuses
  • Generous equity grant
  • Comprehensive medical, vision, and dental benefits
  • Fully remote work environment
  • Flexible paid time off (PTO) policy
Full Job Description
About the RoleWe'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.

What You'll Do
  1. Team Leadership & Development
    • 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
  2. Technical Architecture & Data Platform Ownership
    • 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
  3. Product Management & Stakeholder Enablement
    • 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

What We're Looking For
  1. Experience:
    • 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
  2. Technical Skills:
    • Modern Stack: Deep expertise in cloud data warehouses (e.g., Snowflake), orchestration tools (e.g., Airflow), and ingestion tooling (e.g., Fivetran)
    • Analytics Engineering: Mastery of dbt and core analytics engineering practices - data modeling, semantic layer design, testing, and documentation best practices
    • Governance & Security: Practical experience designing role-based access control (RBAC) frameworks, PII/PHI tokenization, masking, and automated access control systems
  3. Leadership & Communication:
    • 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

Benefits (for U.S.- based full-time employees)
  • Competitive Base Salary + Bonus
  • Generous equity grant
  • Medical, vision, and dental benefits
  • Fully remote company
  • Flexible PTO

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