About Bree
Bree is a consumer finance platform that brings better, faster, and cheaper financial services to over half the Canadian population who live paycheck to paycheck. We operate in a huge, but overlooked market in a country with the least amount of financial technology innovation among the developed world. Our first act is becoming the cheapest and best provider of short-term credit to the 20 million people in Canada who live paycheck to paycheck.
More than 400,000 Canadians have already signed up with Bree and we believe we are just scratching the surface. We are in an exciting place where we have product market fit, explosive growth, and a clear path to becoming one of the most important FinTechs in Canada.
We are at 8-figures of annualized revenue, growing double-digit monthly, profitable, and have had 0 voluntary employee churn. We were part of Y Combinator in 2021 and raised a $2M seed round shortly after.
About the Role
We’re looking for a Data Engineer to design, build, and optimize scalable data infrastructure. You’re passionate about data architecture, pipeline efficiency, and enabling data-driven decision-making at scale. Your work will power analytics, machine learning, and operational insights across the company.
What You'll Do
Design, develop, and maintain robust ETL/ELT pipelines for processing structured and unstructured data.
Build and optimize data warehouses and lakehouses for high-performance analytics and machine learning workloads.
Develop and maintain batch and real-time data pipelines using tools like Apache Airflow, AWS Glue, and Kafka.
Implement data modeling best practices, including star and snowflake schemas for efficient query performance.
Optimize PostgreSQL and other relational databases for scalability and high availability.
Work with AWS services (RDS, Redshift, S3, Lambda, Glue, Athena) to architect and maintain scalable data infrastructure.
Ensure data quality, governance, and security by implementing best practices in logging, monitoring, and access controls.
Collaborate with ML engineers to provide efficient data pipelines for machine learning training and inference.
Deploy infrastructure as code (Terraform, CloudFormation) to automate data infrastructure management.
What You'll Need
Proficiency in SQL and deep experience with PostgreSQL and other relational databases.
Strong expertise in AWS data engineering, including RDS, Redshift, Glue, and Lambda.
Track record of building and maintaining data warehouses for analytics and machine learning.
Experience with data pipeline orchestration tools (Apache Airflow, Dagster, Prefect).
Knowledge of distributed computing and big data frameworks (Spark, Hadoop, Snowflake).
Experience implementing MLOps practices, supporting model training and inference pipelines.
Strong programming skills in Python and SQL for data transformation and automation.
Understanding of data governance, lineage, and compliance best practices.
Ability to optimize and maintain real-time data streaming architectures (Kafka, Kinesis).
Problem-solving mindset with the ability to translate business needs into scalable data solutions.
Benefits
Top of the market compensation for top performers
Comprehensive dental / vision
$1,500 annual learning stipend
$1,000 annual wellness stipend
$250 monthly lunch stipend
2 annual company retreats
Parental leave
Unlimited PTO