Data Analyst, Brex

• 3+ years of experience in data analytics or a related role in a professional setting
• 2+ years of experience working directly with Sales, Operations, Product, or equivalent business teams
• Fluency in SQL to manipulate data and perform complex analyses (CTEs, window functions, joins across large datasets)
• Experience with Python for data analysis, automation, or scripting
• Experience with business intelligence and data visualization tools (Looker, Hex, Tableau, or similar)
• Strong quantitative and analytical skills with a demonstrated ability to translate data into business insights
• Strong communication skills and the ability to work effectively with stakeholders across different functions and levels of technical fluency
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools

Desirable

• The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations
• Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company
• As a Data Analyst II (DA), you will play a central role in enhancing the operational tracking and reporting capabilities of different business teams across Brex
• You will work closely with Data Scientists, Data Engineers, and partner teams to drive meaningful insights for the business through visualizations, self-service tools, and ad-hoc analyses. This is a high-impact role in a fast-paced fintech environment where your work will directly influence strategic decisions
• Apply data visualization and storytelling skills in creating business intelligence solutions (such as Looker and/or Hex dashboards) that enable actionable insights
• Perform ad-hoc analyses and deep dives to investigate business questions, surface trends, and provide data-driven recommendations
• Develop self-service data tools and processes that empower business stakeholders to independently monitor the performance and health of their respective areas
• Collaborate closely with Data Scientists and Data Engineers to identify data sources, enable data pipelines, and support the development of analytical data models that operationalize reports and dashboards
• Implement and maintain rigorous data quality checks to ensure the integrity and robustness of datasets used across dashboards, reports, and analyses
• Partner with various departments—including Sales, Operations, Product, and Finance—to understand their data needs and deliver tailored analyses and reporting that support strategic planning
• Contribute to the automation of recurring analyses and reporting workflows using Python