Finance Analytics Manager

Role Overview

• Own the GTM analytics infrastructure — build and maintain the data models and reporting frameworks that power revenue forecasting, customer acquisition tracking, and ad hoc GTM analytics initiatives
• Lead KPI stewardship across the full customer lifecycle — develop and maintain consistent metric definitions and data structures for ARR, GRR, NRR, CAC, LTV, payback period, conversion rates, and other core SaaS metrics, ensuring alignment between how metrics are defined operationally and how they are used in financial models and forecasts
• Design, execute, and measure GTM experiments — structure A/B tests, build the analytical frameworks to evaluate them, and quantify the financial impact of different approaches
• Build and maintain dashboards and reporting tools that deliver timely, trusted GTM and revenue performance visibility to Finance, Revenue Operations, and executive leadership
• Write and optimize complex SQL queries to extract and transform large datasets from core systems (billing, CRM, product, data warehouse) into clean, analysis-ready outputs
• Collaborate with FP&A, Accounting, Revenue Operations, BI, and Data Engineering to align on data sources, metric definitions, and reporting standards
• Drive the development of scalable, automated analytics processes, improving accuracy, efficiency, and speed-to-insight across Finance
• 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, helping elevate analytical rigor and consistency as the company scales toward public-company readiness

Requirements

• 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) strongly preferred
• Hands-on experience designing and measuring experiments — structuring A/B tests, defining success metrics, and quantifying the financial impact of results
• Deep understanding of financial data structures, SaaS metrics (ARR, NRR, CAC, LTV, conversion/retention, retention and cohort analyses), and concepts related to revenue, billing, and expense modeling
• Experience with BI and visualization tools (e.g., Tableau, Looker, Power BI) and FP&A platforms (e.g., Abacum, Pigment)
• Proven ability to partner cross-functionally with technical and non-technical stakeholders to deliver scalable data solutions
• Excellent analytical and problem-solving skills; able to structure and communicate complex financial data clearly and persuasively
• Strong attention to detail, organization, and ability to manage multiple priorities in a fast-paced environment.

Tech Stack

• SQL
• Tableau