Role Overview

As a Lead Data Analyst, you will provide strategic insights and translate complex data into narratives that drive our global Finance & Strategy decisions. You will collaborate across Finance & Strategy to build high-impact, data-driven models and analytics to enable rapid decision-making. While your primary focus is on strategic analysis, you will also design and govern an Analyst-Ready Data Layer that is the foundation for analytics across the team. By combining deep SaaS business context with technical data engineering, you ensure our insights are not only impactful but built on a scalable, audit-ready infrastructure.

Key Responsibilities

• Revenue Cycle & Predictive Modeling: Optimize the opp-to-cash journey by analyzing ARR-to-revenue conversion rates and renewal patterns, while building early-warning indicators to signal risks and opportunities in the long-term outlook.
• SaaS Unit Economics & Business Diagnostics: Lead advanced analytics on core business drivers, correlating hosting costs and service delivery against gross margins while modeling consumption-based indicators to identify proactive upsell and churn risks.
• Executive Storytelling: Partner with finance leadership to evolve and elevate the delivery of professional reporting packages for internal leadership and investment partners, ensuring monthly business reviews and board decks are supported by clear, intuitive narratives.
• Analyst-Ready Data Layer Architecture: Design and govern a dedicated business data layer by transforming raw data from systems like NetSuite, Salesforce, and Coupa into functional, high-performance schemas that eliminate manual data preparation for the global team.
• Technical Innovation & Partnership: Serve as the primary bridge to central Data Engineering to influence warehouse schema design while piloting AI-driven concepts to automate data anomaly detection and streamline the analytical pipeline.

The Profile

• Experienced Strategist: 8+ years of experience in data analytics, engineering, or database architecture, with a proven track record of supporting complex financial or business modelling.
• SaaS Industry Expertise: Deep understanding of high-growth SaaS environments and the specific data structures required to model subscription-based metrics like ARR, CAC, and LTV.
• Advanced Analytics & Visualization Toolkit: Expert proficiency with modern BI platforms (e.g., Tableau, Power BI, or Looker) to transform the Analyst-Ready Data Layer into interactive executive dashboards. Mastery of advanced Excel or Google Sheets for high-rigor financial modeling is essential.
• Technical Power User: Mastery of advanced SQL and deep experience navigating modern data warehouse environments to move data from raw sources into functional models.
• Bridge Builder: Exceptional at translating complex business needs from business leaders into technical execution and high-performance data schemas.

Job Description: Sr Manager, Finance Data & Analytics

About the Job

As the Sr Manager of Finance Data & Analytics, you lead the engine room that powers our strategic decision-making. Your success is defined by the winning combination of partnering your team’s technical data expertise with the business context of our other Finance functions to maximize insights for the executive team. You are responsible for delivering data analytics and the high-confidence Analyst-Ready Data Layer, ensuring our organization executes on insights.

Key Responsibilities

• Data Analysis & Insights: Lead high-impact, cross-functional analyses to uncover the why behind business results, identifying hidden trends and providing strategic recommendations across both top-line growth and expense management.
• Predictive Analytics: Develop and refine early warning indicators that signal structural risks or opportunities in the long-term outlook before they hit the P&L.
• Executive Decision Support: Synthesize complex data analytics into clear, actionable narratives for the CEO, CFO, and PE partners, acting as a strategic advisor to the VP of Finance & Strategy.
• Partnerships & Insights: Actively partner with the Finance & Strategy team on high-priority projects, combining deep data mining with functional business context to deliver more impactful insights.
• Analyst-Ready Data Layer: Build and govern a dedicated business data layer, utilizing both structured warehouse schemas and agile ad-hoc tables, to provide a foundational data layer that eliminates manual data prep, allowing every analyst to work efficiently.
• Connected Planning:  Oversee the integrated architecture of our planning environment (Pigment), ensuring that functional models remain synchronized without sacrificing the autonomy of individual teams.
• Finance AI & Innovation Roadmap: Act as the Finance lead for emerging AI/ML technologies in the finance space; evaluate and pilot AI-driven concepts to enhance forecasting capabilities, automate data anomaly detection, and streamline the Analyst-Ready data layer as the technology matures.

The Profile

• Strategic Partner: 8–10+ years in Finance or Analytics at a $100M+ SaaS company, with a mastery of recurring revenue economics, customer lifecycles, and the data structures required to model complex subscription metrics.
• Bridge Builder: Exceptional at communicating technical data concepts to non-technical audiences.
• Technological Curiosity: A forward-thinking mindset regarding the evolution of technology and Finance; you have a pulse on how Generative AI and Machine Learning are transforming data analysis and can pragmatically apply these tools to solve business problems.
• Data Supported Rigor: You thrive in environments where data accuracy, auditable definitions, and analytical integrity are the standard.

• Advanced SQL & Solution Design: High proficiency in advanced SQL for complex data manipulation to ensure a robust business data layer. 
• Data Governance & Quality:  Proven ability to implement data hygiene protocols and traceability in the transformation layer to guarantee that financial outputs are valid and audit-ready.
• DWH Partnership: Deep experience partnering with Data Engineering and Data Warehouse teams to influence data ingestion priorities and schema designs that support scalable financial modeling.

Analytical Storytelling: Expert at using tools like Tableau to turn the engineered data layer into compelling narratives for leadership.

About the Role

As a Senior Data Engineer, you are a vital builder within our Finance "Engine Room". Your mission is to develop and maintain the technical infrastructure that is our Analyst-Ready Data Layer. You will execute on the strategic enablement layer, leveraging the enterprise data warehouse and ad-hoc solutions to facilitate fast-paced diagnostic, descriptive, and predictive analytics. Your work ensures that data is enriched, structured, and reliably delivered to reveal the underlying drivers of business performance for our global Finance & Strategy team.

Key Responsibilities

• Business Data Execution: Develop and maintain the dedicated business data layer, utilizing structured warehouse schemas and agile ad-hoc tables to eliminate manual data prep and ensure a ready-to-use foundation for analysis.
• Operationalizing Logic: Partner with the Data Engineering teams to migrate mature, ad-hoc financial logic into standardized, enterprise production pipelines.
• Upstream Quality Support: Collaborate with source-system owners to implement data-entry improvements and hierarchy audits, ensuring data hygiene and productivity at the point of creation.
• Advanced SQL Development: Utilize advanced SQL for complex data manipulation to build and optimize data structures that specifically support SaaS financial modeling, such as ARR waterfalls and OpEx leverage.
• Integrity & Traceability: Maintain rigorous data hygiene protocols and transformation-layer traceability to guarantee that financial outputs are valid, auditable, and board-ready.
• Finance AI & Innovation Support: Assist in the technical implementation of AI-driven concepts and LLM solutions to automate data anomaly detection and streamline the "Analyst-Ready" pipeline as our technology matures.

The Profile

• Experienced Data Engineer: 5–7+ years in data engineering or database development, with a strong background in building data layers for complex business or financial modeling.
• SaaS Industry Expertise: Proven track record in a high-growth SaaS environment, with a deep understanding of the data relationships required to model recurring revenue (ARR), customer lifecycles, and subscription-based metrics.
• Strategic Business Data Leader: Proficiency in Salesforce, NetSuite, and other finance and HR system data relationships to bridge the data architecture with SaaS business context to ensure data structures directly power F&S analytics and critical metrics. 
• Technical Power User: Proven advanced SQL knowledge and deep experience with modern data warehouse environments; you understand how to transform raw data into functional business models.