Senior Manager - Analytics Engineering

Role Description

We're looking for a Senior Manager of Analytics Engineering to lead the team responsible for building the trusted data foundation, i.e. semantic metrics layer, that powers decision-making across the company. You'll oversee a team of analytics engineers who transform raw data into scalable, reliable, and well-governed data models that enable self-service analytics, operational reporting, experimentation, and AI-driven products.

As a cross-functional leader, you'll partner closely with Engineering, Product, Data Science, Finance, Marketing, Sales, Customer Success, and Executive Leadership to define our data strategy and ensure high-quality, accessible data at scale. You'll balance technical excellence with business impact, helping the organization become increasingly data-driven while building a high-performing and inclusive team.

Responsibilities

• Leadership & Team Management
  • Hire, develop, and lead a high-performing team of Analytics Engineers
  • Foster a culture of technical excellence, ownership, continuous learning, and collaboration
  • Provide coaching, career development, and regular performance feedback
  • Establish team goals, operating rhythms, and execution processes that align with company priorities to deliver business impact
• Analytics Engineering Strategy
  • Define and execute the roadmap for analytics engineering, data modeling, semantic layers, and analytics infrastructure
  • Build scalable dimensional models and curated datasets that enable trusted reporting and advanced analytics
  • Drive adoption of analytics engineering best practices including testing, documentation, version control, CI/CD, and code review
  • Own data quality initiatives, observability, lineage, and governance across the analytics ecosystem
  • Continuously improve developer productivity and platform scalability
• Cross-Functional Partnership
  • Partner with peers on the Data team and business stakeholders to understand evolving analytical needs and translate them into scalable data products
  • Collaborate with Data Engineering to improve data pipelines, ingestion, orchestration, and warehouse performance
  • Work alongside Product Analytics & Data Science to enable experimentation, machine learning, and advanced analytics
  • Support Finance and Executive Leadership with trusted metrics and executive reporting
  • Help establish company-wide metric definitions and ensure consistency across teams
• Technical Leadership
  • Set standards for data modeling, transformation, documentation, and testing
  • Guide architectural decisions for the analytics stack and evaluate new technologies
  • Ensure analytics infrastructure scales with rapid business growth
  • Review technical designs and mentor engineers through complex implementation challenges
  • Champion automation, reliability, and engineering best practices throughout the data organization
  • Thinks strategically while remaining execution-oriented, making pragmatic trade offs between speed, scalability, and technical debt
  • Builds trust through transparency and strong communication, delegating to and developing future technical leaders
  • Thrives in fast-moving, ambiguous environments and helps others navigate change

Qualifications

• 11+ years of experience in analytics engineering, business intelligence, data engineering, or related fields
• 3+ years managing high-performing technical teams, growing and developing people
• Deep expertise with SQL and modern analytics engineering practices
• Experience building analytics platforms using DBT, Snowflake, Airflow or similar orchestration tools
• Familiarity with Git and CI/CD workflows and BI platforms
• Strong understanding of dimensional modeling, semantic layers, and data warehousing concepts
• Experience defining data governance, testing, and data quality frameworks
• Excellent stakeholder management and communication skills
• Demonstrated ability to influence technical strategy across multiple organizations

Nice to Have

• Experience partnering with accounting/close the books procedures at a public company
• Experience managing audit processes and governance programs is a plus
• Experience at a high-growth SaaS or technology company
• Experience scaling analytics organizations through rapid company growth
• Familiarity with event-driven data architectures and product analytics
• Experience supporting experimentation platforms and machine learning initiatives
• Knowledge of metrics governance and executive KPI frameworks

Benefits