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