Responsible for building the analytics foundation connecting product usage to business outcomes. Analyze product usage, engineering efficiency, and AI adoption impact while synthesizing insights for leadership and strategic decisions.
About Us
HighLevel is an AI powered, all-in-one white-label sales & marketing platform that empowers agencies, entrepreneurs, and businesses to elevate their digital presence and drive growth. We are proud to support a global and growing community of over 2 million businesses, comprised of agencies, consultants, and businesses of all sizes and industries. HighLevel empowers users with all the tools needed to capture, nurture, and close new leads into repeat customers. As of mid 2025, HighLevel processes over 4 billion API hits and handles more than 2.5 billion message events every day. Our platform manages over 470 terabytes of data distributed across five databases, operates with a network of over 250 microservices, and supports over 1 million hostnames.
Our People
With over 1,500 team members across 15+ countries, we operate in a global, remote-first environment. We are building more than software; we are building a global community rooted in creativity, collaboration, and impact. We take pride in cultivating a culture where innovation thrives, ideas are celebrated, and people come first, no matter where they call home.
Our Impact
As of mid 2025, our platform powers over 1.5 billion messages, helps generate over 200 million leads, and facilitates over 20 million conversations for the more than 2 million businesses we serve each month. Behind those numbers are real people growing their companies, connecting with customers, and making their mark - and we get to help make that happen.
Role Overview
We’re looking for a Lead - Strategy and Analytics to sit at the intersection of Product Analytics, Engineering Analytics, and Business Insights. You will be responsible for building the analytics foundation that not only connects product usage to business outcomes, but also tracks engineering efficiency and AI adoption impact. You’ll be hands-on with data — querying, modelling, and building dashboards — while partnering with leadership to shape the narrative of how product development efficiency and product adoption fuel business success.
Key Responsibilities
Product Analytics
- Analyse product usage, trial-to-paid funnels, adoption of new features, retention, and churn.
- Build dashboards for feature adoption and monetisation.
- Connect product engagement data to key business KPIs (ARR, NRR, LTV:CAC).
Engineering & AI Analytics
- Partner with Engineering leadership to analyse developer productivity and operational metrics (velocity, DORA metrics, throughput, cycle time).
- Track AI adoption efficiency across the product development lifecycle (AI tools in workflows, adoption of AI-powered features, ROI on AI initiatives).
- Provide insights into how engineering efficiency translates into product velocity and business outcomes.
Data Governance & Consistency
- Define consistent KPI frameworks across Product, Engineering, and Finance.
- Establish best practices for metric definitions, documentation, and cross-team alignment.
- Ensure alignment on core metrics: active accounts, churned accounts, developer efficiency benchmarks, AI feature adoption.
- Contribute to a single source of truth for org-wide metrics.
Strategic Insights & Storytelling
- Synthesize findings into clear and compelling narratives for leadership, the board, and (eventually) IPO investors.
- Build executive-ready reports and dashboards that inform business decisions and performance reviews.
- Translate technical data (engineering metrics, AI adoption) into business-relevant insights.
- Partner with cross-functional leaders to drive data-backed decision-making.
Qualifications
- 8 years+ of experience in Data Analytics, Product Analytics, or BizOps (SaaS required).
- Strong expertise in SQL, and working with data warehouses (Snowflake, BigQuery, Clickhouse).
- Strong hands-on analytics skills: SQL, data modelling, BI tools like Tableau.
- Experience working with engineering productivity data (Clickup, GitHub, DORA metrics tools).
- Familiarity with AI adoption metrics (AI feature usage tracking, internal developer AI tool usage, ROI measurement).
- Knowledge of SaaS metrics: ARR, NRR, GRR, CAC, LTV, cohort retention.
- Proven ability to stitch together multiple data domains (product usage + engineering + finance).
- Excellent communication and storytelling skills — can distil complex analyses into executive-ready narratives.
- Bonus: Experience with Python/R for advanced modelling and experimentation.
What You’ll Bring
- A hands-on builder who thrives on solving data puzzles across different domains.
- A connector who links product adoption, engineering efficiency, and business growth.
- A storyteller who makes technical and product development data accessible to non-technical stakeholders.
- A strategic partner who ensures analytics support HighLevel’s IPO journey.
Why Join HighLevel?
- Influence both product strategy and engineering efficiency at a SaaS company.
- Directly shape how HighLevel tells its IPO story to investors.
- Work across Product, Engineering, and Finance at the highest levels.
- Be at the forefront of AI adoption analytics in SaaS.
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.
#LI-Remote #LI-MP1
Top Skills
BigQuery
Clickhouse
Python
R
Snowflake
SQL
Tableau
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