Data Engineer

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.

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.

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!

• 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.

• Use agentic AI where it speeds up pipeline and quality work, without skipping validation.

• 3+ years of experience in Data Engineering, Data Analytics, or a related field such as Analytics Engineering.

• 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.

• Strong communication skills and ability to collaborate with various stakeholders, both technical and non-technical.

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

• Solid dbt in production: models, tests, docs, and collaboration in a shared repo.

• AI-ready data: Metrics and dimensions are clear and reusable so AI-assisted analysis does not fork definitions.

The expected salary range for this role is $120,800 - $151,000. 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.