Senior Finance Analytics Manager | United States | Remote

What You’ll Be Doing

Data Modeling & Architecture: Partner with distributed data teams to build, iterate, and optimize our corporate data architecture. Develop reliable data models to help define company-wide performance metrics, tracking them seamlessly from raw source data down through user-friendly reporting layers.

Dashboards & Reporting: Design, build, and maintain production-quality dashboards and scalable data products. Establish reliable, automated tooling that allows internal stakeholders to monitor key operating metrics in real-time.

Advanced Analytics & Deep Dives: Build advanced analytical models to unlock deeper insights into customer behaviors and macro trends, mapping operational opportunities directly to financial outcomes.

Executive Storytelling: Synthesize complex data and analyses into compelling, structured narratives and actionable insights for executive consumption and senior leadership decision-making.

Enablement & Governance: Lead cross-functional projects to develop datasets that support the organization's evolving needs; provide documentation and continuous enablement to help finance and business teams self-serve basic data needs.

Operational Excellence: Set a high bar for analytics integrity across the organization by managing urgent, ad-hoc data analysis requests and maintaining rigorous QA support for core financial data.

What Makes You a Great Fit

Professional Experience: 5+ years of experience in corporate analytics, financial analytics, data science, or a directly related quantitative field. Experience in a fast-paced technology or SaaS business is highly preferred.

SQL Mastery: 5+ years of hands-on SQL experience, with a daily habit of writing complex, highly efficient queries to mine data and build production-ready data models.

Data Visualization: 3+ years of experience building user-focused, production-quality dashboards in tools like Looker, Tableau, Mode, or Sisense. Previous experience with Grafana visualization, or a strong desire to invest the time to learn it, is a major plus.

Data Stack & Architecture: Practical experience performing data model development, building ETL processes, and working within modern data warehouses (e.g., BigQuery, Snowflake). Familiarity with dbt is highly desirable.

Business Systems: Familiarity with core enterprise systems and data structures, specifically NetSuite and Salesforce, to understand how financial and operational data flows from the source to reporting layers.

Executive Communication: Exceptional communication skills with a proven track record of translating complex analysis into structured narratives for senior management. You can seamlessly explain "what the data is," "why it matters," and "what we should do about it."

Analytical Balance: Strong critical reasoning and financial modeling skills. You understand the common pitfalls of data analysis, know how to track core SaaS metrics (ARR, NDR, retention), and can map operational trends directly to financial outcomes.

Bonus Points For

Industry & Scale Context: Experience working in a high-growth SaaS, cloud, or open-source company, particularly within a public company or an environment undergoing IPO readiness.

Global Collaboration: Proven success working within globally distributed, remote-first organizations across multiple time zones.

AI & LLM Data Preparation: Experience documenting datasets and optimizing tooling for Model Context Protocol (MCP) server ingestion, or constructing AI skills and plugins to enable automated, LLM-driven internal data discovery.

Compensation and Rewards

In the United States, the base compensation range for this role is $143,759 - $172,511. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success.