Data Engineer

Brex • New York, NY

2h • Hybrid

About The Position

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 Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it's more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using data. Our work is ingrained in Brex's decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our customers. What You’ll Do As a Data Engineer at Brex, you will be a core contributor in transforming raw data into actionable insights for various departments across the organization. You'll collaborate closely with Data Scientists, Software Engineers, and business units to create efficient data models, pipelines, and analytics frameworks that drive the business forward. You also play a leading role in the design, implementation, and maintenance of Core Data tables, our high-quality, curated data source for a wide range of analytic applications. Where you’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 two coordinated days in the office per week, Wednesday and Thursday. Starting February 2, 2026, we will require three days per week in office - Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Requirements

• 3+ years of experience in Data Engineering, Data Analytics, or a related field such as Analytics Engineering.
• 2+ years of experience working with modern data transformation tools like DBT.
• Advanced knowledge of databases and SQL with the ability to efficiently stage, process, and transform data.
• Experience integrating and orchestrating data workflows with various modern data tools and systems.
• Experience with data modeling, ETL/ELT processes, and data warehousing solutions.
• Experience working with a data warehouse such as Snowflake.
• Experience with a data workflow orchestrator tool such as Airflow.
• Experience with a programming language such as Python.
• Exceptional quantitative and analytical skills.
• Strong communication skills and ability to collaborate with various stakeholders, both technical and non-technical.

Nice To Haves

• Familiarity with BI tools such as Looker, Tableau, or similar platforms is a plus.

Responsibilities

• Design, build, and maintain data models and pipelines that scale with the growing number of services, products, and changes in the company.
• Collaborate closely with Data Scientists, Data Analysts, and Business teams to understand their data needs, translating them into robust, efficient, scalable data solutions that enable ease of predictive analytics, data analysis, and metrics formulation.
• Maintain data documentation and definitions, building and ensuring that source-of-truth tables remain high quality for data science and reporting applications.
• Develop and enable integration with various data sources, allowing for more data-driven initiatives across the company.
• Apply best practices in data management to ensure the reliability and robustness of data utilized across various analytics applications.
• Set and proliferate company-wide standards for data relating to structure, quality, and expectations.
• Act as a liaison between the technical and non-technical teams, bridging gaps and ensuring that data solutions align with business objectives.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 1,001-5,000 employees