Data Analyst III at Brex

San Francisco, California, United States -

Full Time

Start Date

Immediate

Expiry Date

13 Jun, 26

Salary

142740.0

Posted On

15 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, Data Modeling, Statistical Methods, Stakeholder Management, Data Visualization, A/B Testing, dbt, Airflow, Git, Snowflake, Looker, Tableau, Pandas, NumPy, Scikit-learn

Industry

Financial Services

Description

Why join us Brex is the AI-powered spend platform. We help companies spend with confidence with integrated corporate cards, banking, and global payments, plus intuitive software for travel and expenses. Tens of thousands of companies from startups to enterprises — including DoorDash, Flexport, and Compass — use Brex to proactively control spend, reduce costs, and increase efficiency on a global scale. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Data at Brex 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. What you’ll do As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex. You’ll go beyond building dashboards—you’ll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership. You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team’s work. This role sits at the intersection of analytics, analytics engineering, and business strategy. You’ll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization. Where you’ll work This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work! Responsibilities Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation. Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions. Write production-quality SQL and Python code to extract, transform, and analyze data at scale. Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization. Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations. Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks. Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes. Requirements 5+ years of experience in data analytics, business intelligence, or a related quantitative role. 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner. Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models. Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar). Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued). Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar). Strong stakeholder management skills—proven ability to present complex technical findings to non-technical audiences. 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. Bonus points Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing). Experience with dbt for data modeling and transformation. Experience building and maintaining data pipelines using orchestration tools such as Airflow. Experience working with APIs for data ingestion and integration. Familiarity with version control systems (Git). Experience in fintech, financial services, or payments. Track record of leading cross-functional analytics projects from scoping through delivery. Compensation The expected salary range for this role is $114,192 - $142,740. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package. Please be aware, job-seekers may be at risk of targeting by malicious actors looking for personal data. Brex recruiters will only reach out via LinkedIn or email with a brex.com domain. Any outreach claiming to be from Brex via other sources should be ignored.

Responsibilities

The Senior Data Analyst will own the end-to-end analytics lifecycle for assigned business areas, framing questions, designing rigorous analyses, and translating findings into clear recommendations for leadership. They will also serve as a technical leader by mentoring junior analysts and defining team standards and best practices.