Risk Analytics Engineer: Data Pipelines & Modeling

Socket.dev; Toronto; On-site; CAD 80,000 - 110,000; Full time

Job summary

Propel is building a fintech platform that evaluates credit risk with AI-driven data pipelines. As Analytics Engineer, Risk, you will own data integration, ETL design, and production pipelines to support model training, scoring and monitoring.

You will work closely with Data Scientists, Model Developers, and Infrastructure to ensure scalable, auditable data flows. You will work in Python and SQL, handling tabular and time-series data, and collaborate across regions CA/US/UK to standardize data

Qualifications

• Bachelor’s degree or equivalent in a quantitative field
• 3+ years of hands-on Python skills and production-quality code
• Familiarity with pandas, NumPy, and scikit-learn
• Experience building or maintaining ETL/data pipelines
• Proficiency with Git and CI/CD practices
• Strong collaboration with Data Scientists and Engineers
• Fintech/credit risk experience is a plus

Responsibilities

• Own integration of new data sources into model-ready data standards across CA/US/UK
• Design, build, and maintain ETL pipelines for model training, retraining, and scoring
• Build pipelines within the shared ETL/orchestration framework for rapid onboarding of new models
• Develop feature engineering and data transformation logic for tabular/time-series data
• Monitor data pipelines for health, quality, and drift; resolve issues
• Write clean, production-grade Python code and reusable modules
• Work with Docker, Kubernetes, AWS, and S3 for deployment and storage
• Query data from relational DBs and data warehouses using SQL
• Document data sources, pipeline logic, and transformations
• Collaborate with Data Scientists, Model Developers, and Infrastructure teams

Skills

Python

SQL

ETL pipelines

Airflow

Pandas

NumPy

scikit-learn

Git

CI/CD

Data modeling

Education

Bachelor’s degree in computer science, data engineering, statistics, mathematics, or a related quantitative field

Tools

Docker

Kubernetes

AWS

Airflow

Job description

Propel is building a fintech platform that evaluates credit risk with AI-driven data pipelines. As Analytics Engineer, Risk, you will own data integration, ETL design, and production pipelines to support model training, scoring and monitoring.

You will work closely with Data Scientists, Model Developers, and Infrastructure to ensure scalable, auditable data flows. You will work in Python and SQL, handling tabular and time-series data, and collaborate across regions CA/US/UK to standardize data