About Us Propel (TSX: PRL) is the fintech company building a new world of financial opportunity by facilitating access to credit for consumers underserved by traditional financial institutions. Through its AI-driven platform, Propel evaluates customers in a more comprehensive way than traditional credit scores can. Our revolutionary fintech platform has already helped consumers access over one million loans and lines of credit and over one billion dollars in credit.
To build a current world of opportunity we bring together the brightest talent to help us build opportunities. We are entrepreneurs and believe in measuring success through results and growing within; talent and hard work never goes unnoticed. At Propel, we are here to change the way employees, customers and shareholders succeed together.
We are a team of passionate entrepreneurs, who foster curiosity and growth in our employees. Our culture is why we have been so successful and why our employees choose Propel to build their careers. It is also why we are one of North America’s fastest growing companies and a Best Place to Work.
Join us as we change the way employees, customers and shareholders succeed together.
About You You thrive in a vibrant, entrepreneurial organization where your ideas are valued. You are motivated by goals, a self-starter, and enjoy wearing multiple hats in a fast-growing fintech environment.
You are a builder at heart—someone who prefers creating reliable data pipelines over another dashboard. You thrive on owning the “plumbing” that delivers clean, timely data to machine learning models and enjoy turning manual, messy processes into repeatable automation. As the Analytics Engineer, Risk, you’ll join the Model Development team within Risk, working closely with the Manager, Model Development, Data Scientists, and Model Developers. This highly technical, hands‑on role focuses on the data infrastructure supporting credit risk models, including ETL pipelines for model training and scoring, standardized ingestion of recent data sources—including UK data—and day‑to‑day delivery of stable production data. You’ll work primarily in Python and SQL with tabular, time‑series, and, as we grow, graph‑structured data such as Neo4j.
Responsibilities Own the integration of new data sources, into Propel’s model-ready data standards, ensuring consistent schemas, definitions, and quality across regions (CA/US/UK)
Design, build, and maintain ETL pipelines that prepare and deliver data for model training, retraining, and scoring across multiple model types, including survival, classification,



and regression models
Build and maintain pipelines within the shared ETL/orchestration framework for model development, following the templates and patterns established by the Model Development team so new models can be onboarded quickly
Build feature engineering and data transformation logic for tabular and time-series data, using tools such as tsfresh or similar
Monitor the health and stability of data pipelines feeding models in production; proactively identify and resolve data drift, quality issues, and pipeline failures
Write clean, well-tested, production‑grade Python code, including scripts and reusable packages or modules, that other team members can build on
Work with containerized model deployments using Docker and Kubernetes, as well as cloud infrastructure such as AWS and S3 for data storage and workflow orchestration, with support from our Infrastructure team
Query and transform data from relational databases and data warehouses using SQL.
Document data sources, pipeline logic, and transformations clearly so pipelines are auditable, maintainable, and easy to hand off
Collaborate closely with Data Scientists and Model Developers to translate model requirements into scalable, production‑ready data pipelines, and with the Business Analytics Engineering and Infrastructure teams where pipelines intersect with broader data platform work
Requirements Must Have Bachelor’s degree in computer science, data engineering, statistics, mathematics, or a related quantitative field
Minimum of 3 years of hands‑on Python skills and comfortable writing production-quality, testable, reusable code
Familiarity with common data and ML libraries such as pandas, NumPy, and scikit‑learn
Experience building or maintaining ETL or data pipelines
Experience with pipeline or workflow orchestration tools such as Metaflow, Airflow, Prefect, Dagster, or similar is a plus
Comfortable working with different data shapes: tabular and time‑series data
Solid SQL skills for querying and transforming data into relational databases such as MySQL and/or data warehouses
Understanding of the ML data lifecycle, including feature engineering, training and scoring data preparation,



and model monitoring and drift concepts
Experience with version control using Git and basic CI/CD practices
Strong communication and collaboration skills, with the ability to work closely with Data Scientists, Model Developers, and Infrastructure/Engineering stakeholders
Experience in fintech, credit risk, or another regulated or data‑intensive industry is a plus
Experience using generative AI tools such as ChatGPT, Claude, or Copilot to accelerate day‑to‑day engineering work is an asset
Nice to Have Exposure to graph data or graph databases such as Neo4j (nice‑to‑have)
Snowflake experience (nice‑to‑have)
Exposure to Docker, containerization, and cloud infrastructure such as AWS, S3, EKS, or similar services (nice‑to‑have)
Benefits To Joining Propel Growth and opportunity – we pride ourselves on promoting from within
Incredible company culture
Competitive salary and health benefits
Comprehensive vacation package
Group health and dental benefits
Group RRSP program
Support for new parents
Diverse and inclusive workplace
Salary Range $70,000 - $100,000
Final compensation is determined by market conditions, location, and the candidate’s experience, skills, and education. This role may also be eligible for performance‑based incentive programs and total compensation may include variable incentives, such as bonuses and commissions.
This posting is for an existing vacancy within our organization.
Our Culture Propel brings together the brightest talent to build opportunities. We are entrepreneurs who measure success through results and growth from within; talent and hard work never go unnoticed. Our team fosters curiosity and growth, making Propel one of North America’s fastest‑growing companies and a Best Place to Work.
Commitment to Diversity & Inclusion Propel welcomes and encourages applications from all groups, including Indigenous peoples, women, visible minorities, persons with disabilities, people from gender and sexually diverse communities, and those with intersectional identities. Should you require accommodation throughout any stage of the recruitment and selection process, please specify your requirements when submitting your application and we will work with you to meet your needs.
AI Disclosure We use AI to assist in reviewing applications and assessing candidates. These tools support our recruitment team, however, all hiring decisions are made by our trained hiring managers and recruitment professionals, not AI.

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📌 Analytics Engineer, Risk (Ontario)
🏢 Propel Holdings
📍 Ontario