HighLevel - Senior Manager
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 • 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 • $194,750 - $261,000 a year
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
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