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About the Role

Propel is seeking an Analytics Engineer, Risk to join the Model Development team. This role focuses on the data infrastructure supporting credit risk models, including ETL pipelines for model training and scoring, standardized ingestion of new data sources, and day-to-day delivery of stable production data. You will work primarily in Python and SQL with various data structures.

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 established templates and patterns.
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.
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.
Query and transform data from relational databases and data warehouses using SQL.
Document data sources, pipeline logic, and transformations clearly.
Collaborate closely with Data Scientists and Model Developers to translate model requirements into scalable, production-ready data pipelines.
Collaborate with Business Analytics Engineering and Infrastructure teams where pipelines intersect with broader data platform work.

Requirements

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.
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).

Skills

Python
SQL
ETL
Data Pipelines
Feature Engineering
Data Transformation
tsfresh
Docker
Kubernetes
AWS
S3
Git
CI/CD
pandas
NumPy
scikit-learn
Metaflow
Airflow
Prefect
Dagster
Neo4j
Snowflake
EKS
Generative AI
ChatGPT
Claude
Copilot

Location

CA/US/UK

Work Type

Full-time

Experience Level

3 years of hands-on Python skills
Minimum of 3 years of experience

Education Level

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

Salary/Compensations

$80,000 - $110,000

Benefits

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

About the Company

Propel is a fintech company building a new world of financial opportunity by facilitating access to credit for consumers underserved by traditional financial institutions.
Propel's AI-driven platform evaluates customers more comprehensively than traditional credit scores.
Propel's revolutionary fintech platform has helped consumers access over one million loans and lines of credit and over one billion dollars in credit.
Propel is a team of passionate entrepreneurs who foster curiosity and growth in employees.
Propel is one of North America’s fastest growing companies and a Best Place to Work.
Propel brings together the brightest talent to build opportunities.
Propel measures success through results and growth from within; talent and hard work never go unnoticed.
Propel is here to change the way employees, customers and shareholders succeed together.

Equal Opportunity

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.