Senior Manager - Analytics Engineering
About The Position
HighLevel is seeking a Senior Manager of Analytics Engineering to lead the team responsible for building the trusted data foundation, specifically a semantic metrics layer, that powers decision-making across the company. This role will oversee a team of analytics engineers who transform raw data into scalable, reliable, and well-governed data models. These models will support self-service analytics, operational reporting, experimentation, and AI-driven products. The position requires a cross-functional leader who will partner with various departments including Engineering, Product, Data Science, Finance, Marketing, Sales, Customer Success, and Executive Leadership to define the company's data strategy and ensure high-quality, accessible data at scale. The role involves balancing technical excellence with business impact, fostering a data-driven organization, and building a high-performing and inclusive team.
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 Haves
- 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
Responsibilities
- 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
- 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
- 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
- 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
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
