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GoHighLevelGoHighLevelUnited States

Senior Manager

Lead a team of analytics engineers building the semantic metrics layer and scalable data models that power company-wide decision making, reporting, experimentation, and AI products. Requires 11+ years analytics engineering experience including 3+ years managing technical teams, deep SQL and DBT/Snowflake expertise, and strong cross-functional stakeholder skills.

Salary not listed
Remote11+ YOEData Engineering

About the role

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

Requirements

  • 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

Skills

SQLdbtSnowflakeAirflowGitCI/CDdimensional modelingsemantic layersData WarehousingData GovernanceData Qualitybi platforms
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