Senior Manager - Analytics Engineering

About HighLevel: HighLevel is an AI-powered business operating system that gives agencies, entrepreneurs and SMBs the infrastructure to build, automate and scale. Today, HighLevel supports SMBs across 150+ countries, fueling community-driven growth rooted in real customer outcomes. To date, businesses operating on HighLevel have generated over $7 billion in ecosystem value, demonstrating the impact of shared infrastructure at scale. By centralizing conversations, automation and intelligence into one system, we help businesses move faster, reduce complexity and execute efficiently. Behind the platform, HighLevel powers more than 4 billion API hits and 2.5 billion message events daily. With 250 terabytes of distributed data, 250+ microservices and over 1 million domain names supported, our architecture is built for performance, resilience and long-term scalability. Our People With over 2,000 team members across 10+ countries, HighLevel operates as a global, remote-first organization built for speed and ownership. We value initiative, clarity and execution, creating space for ambitious people to build systems that support millions of businesses worldwide. Here, innovation thrives, ideas are celebrated and people come first, no matter where they call home. Our Impact Every month, HighLevel enables more than 1.5 billion messages, 200 million leads and 20 million conversations for the more than 1 million businesses we support. Behind those numbers are real people building independence, expanding opportunity and creating measurable impact. We’re proud to be a part of that. Learn more about us on our YouTube Channel or Blog Posts . About the Role: 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 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 EEO Statement: The company is an Equal Opportunity Employer. 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