Compensation
$150K–$195K
Location
Toronto, Canada
Employment Type
Full Time
Department
Data
Overview
As a Data Engineer at Brivex, you’ll build the pipelines and data models that turn millions of card transactions into reliable insights. Your work will power customer-facing reporting, fraud detection, and the internal analytics our teams use to make decisions every day. You’ll join a small, experienced team where your choices about architecture and tooling will have lasting impact.
Responsibilities
You will design, build, and maintain the data infrastructure behind our card issuing and spending platform. Your role includes ingesting data from transaction systems and partner APIs, modelling it for analytics and machine learning, and making sure it is accurate, secure, and available when teams need it. You’ll also help define data standards and mentor other engineers as the team grows.
Build and maintain batch and streaming pipelines for transaction, ledger, and event data.
Design warehouse data models that support reporting, analytics, and risk teams.
Implement data quality checks, monitoring, and alerting across critical datasets.
Work with security and compliance teams to protect sensitive financial data.
Partner with analysts, data scientists, and engineers to deliver new data products.
The Role
As a Data Engineer at Brivex, you’ll help shape a data platform that grows with every new customer and card. We’re looking for someone with 5+ years of data engineering experience, strong SQL and Python skills, and hands-on work with tools such as Spark, Kafka, dbt, and a cloud data warehouse. Experience with payments or other regulated financial data is a strong plus, as is a habit of documenting what you build so others can rely on it.
Key Benefits
At Brivex, we prioritize your growth, well-being, and work-life balance. As part of our team, you’ll enjoy competitive compensation, equity options, a hybrid working model at our Toronto office, and dedicated time for learning and conferences. You’ll work with a talented, supportive team on data challenges that directly affect how businesses around the world manage their money.
