Senior Data Platform Engineer at Brex — owning the data infrastructure powering financial products across an async, multi-source architecture

This role is on Brex's Data Enablement Platform team, which owns the systems that pull data from many async services and operational systems and deliver it to product teams as data-backed products. The JD requires 5+ years in a data infra/platform role, fluency in Kotlin or Kotlin-like languages (Python called out), and hands-on experience with tools like Snowflake, Flink, Airflow, dbt, CDC, and Kafka. It's explicitly hybrid (in-office Mon/Wed/Fri in Seattle) and blends data platform ownership with cross-functional partnership with product, data science, and analytics teams.

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What this interview tests

Data platform and infrastructure ownership: warehousing, streaming, orchestration, observability, governance
Streaming and CDC systems (Kafka, Flink) at production scale
Data orchestration and transformation tooling (Airflow, dbt, Snowflake)
Kotlin/Python fluency for backend and data infra engineering
Partnering with product, data science, and analytics teams to ship data-backed products
Operational ownership: on-call, reliability, and continuous improvement of data architecture

Common question themes

Design a data pipeline that ingests from many async, heterogeneous source systems reliably

Describe a streaming or CDC system you built with Kafka or Flink, including failure handling

Walk through a dbt/Airflow orchestration problem you solved and why you chose that approach

Tell me about translating a product team's data need into a reusable platform capability

How do you approach data access and governance when many teams consume the same data

Describe an on-call incident in a data platform and what you changed afterward

How candidates describe it

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