About us
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
Who You Are:
HighLevel is seeking a Finance Analytics Manager to join our growing FP&A team. This highly visible, hands-on role will serve as the analytical engine behind HighLevel's product financial strategy — translating product and usage data into insights to better understand product performance and how product specific decisions impact core KPI metrics.
You'll sit at the intersection of Finance and Product — writing queries, structuring datasets, and building scalable frameworks that give product leads a precise, trusted view of how product trends and user behavior translate into financial outcomes. You'll partner cross-functionally with FP&A, Product, Accounting, and Business Intelligence to drive accuracy, automation, and insight across our key product and financial metrics.
This is an ideal opportunity for someone who is equal parts technical and financial, thrives in a data-rich SaaS environment, and is energized by digging deep into data to understand the “why” behind trends.
What You Will Do
Own the product finance analytics infrastructure — build and maintain the data models and reporting frameworks that power product performance tracking, feature adoption analysis, and product analytics initiatives
Lead product KPI stewardship — maintain consistent metric definitions and data structures for ARR, GRR, NRR, feature adoption, and retention metrics, ensuring alignment between how metrics are defined at the product level and how they are used in financial models and forecasts
Design, execute, and measure product experiments — structure A/B tests, build the analytical frameworks to evaluate them, and quantify the financial impact of different product approaches and feature investments
Conduct deep analytical dives into product trends — go beyond surface-level reporting to understand the underlying drivers of engagement, retention, expansion, and churn, and translate those findings into clear financial narratives for leadership
Build and maintain dashboards and reporting tools that deliver timely, trusted product performance and revenue visibility to Finance, Product, and executive leadership
Write and optimize complex SQL queries to extract and transform large datasets from core systems (product, billing, data warehouse) into clean, analysis-ready outputs
Drive the development of scalable, automated analytics processes, improving accuracy, efficiency, and speed-to-insight across Finance and Product
Establish and uphold data governance and quality standards within the Finance domain, ensuring a single source of truth for critical metrics used across the business
Champion a data-driven culture within Finance and Product, helping elevate analytical rigor and consistency as the company scales toward public-company readiness
What You Bring
Bachelor’s degree in Finance, Economics, Data Analytics, Computer Science, or a related field
8+ years total, or 6+ years of relevant experience in FP&A, Data Analytics, or a hybrid role within a high-growth SaaS environment
Advanced SQL proficiency required; experience with data warehouses (e.g., Snowflake) and product analytics strongly preferred
Experience with BI and visualization tools (e.g., Tableau, Looker, Power BI)
Hands-on experience designing and measuring experiments — structuring A/B tests, defining success metrics, and quantifying the financial impact of results
Experience conducting open-ended analytical investigations — comfortable starting from a trend or anomaly and independently structuring an analysis to understand its root cause and financial significance
Excellent analytical and problem-solving skills; able to structure and communicate complex financial data clearly
Proven ability to partner cross-functionally with technical and non-technical stakeholders to deliver scalable data solutions
Strong attention to detail, organization, and ability to manage multiple priorities in a fast-paced environment
The salary range for this position is $102000 - $148000 annually.
Equal Employment Opportunity Information
The company is an Equal Opportunity Employer. As an employer subject to affirmative action regulations, we invite you to voluntarily provide the following demographic information. This information is used solely for compliance with government recordkeeping, reporting, and other legal requirements. Providing this information is voluntary and refusal to do so will not affect your application status. This data will be kept separate from your application and will not be used in the hiring decision.
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