Data Analyst III
New York, New York County, New York, 10261, USA
Listed on 2026-07-03
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IT/Tech
Data Analyst, Business Intelligence, Business Systems/ Tech Analyst, Data Engineering
Why join us
Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world‑class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most.
Tens of thousands of the world’s best companies run on Brex, including Door Dash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and Seat Geek.
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 doAs a senior Data Analyst (DA III), you will own the end‑to‑end analytics lifecycle for one or more business areas ’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.
Whereyou’ll work
This role will be based in our New York 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.
- 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, Num Py, scikit‑learn, or similar).
- Experience with cloud data warehouses, particularly Snowflake (Big Query 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, Git Hub Copilot) to perform and accelerate analyses, automated reporting, and build self‑service data tools.
- 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…
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