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Added 1 hour ago
Senior Software Engineer, Backend, AI Labs
Epiq
Toronto, ON · Greater Toronto Area, Canada
Full-time
Added 2 hours ago
AI Architect, Manager
Avanade
Toronto, ON
Full-time
Applying data and analytics to business use cases
Added 2 hours ago
Senior Full Stack Developer (Global Security)
Royal Bank of Canada
Toronto, ON
Full-time
…and builds bespoke solutions supporting threat hunting, cyber analytics, and security operations. As the Senior Full Stack Developer (Global Security), you will be responsible for designing…
Added 3 hours ago
Senior Data Platform Engineer
Norton Rose Fulbright
Toronto, ON
Full-time
Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
Added 3 hours ago
Senior Data Platform Engineer
Norton Rose Fulbright
Calgary, AB
Full-time
Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
Added 3 hours ago
Machine Learning Engineer, VLA & RL - Senior
cyberwave digital agency
Zurich, ON
Full-time
We're looking for a Machine Learning Engineer focused on vision-language-action (VLA) models, reinforcement learning, and cross-embodiment transfer. You'll work on models that turn…
Added 3 hours ago
Principal Data Engineer - Canada
JobGet
Remote, Canada
$160,000 to $190,000 CAD / year
Full-time · Remote
As our Principal Data Engineer, you will help lead the technical direction for how data flows, scales, and powers every decision at JobGet. You’ll own the data architecture behind our…
Added 4 hours ago
Applications Engineer
Husky Technologies
Bolton, ON
Full-time
Apply a data-driven, first-principles approach, leveraging scientific modeling, experimentation, and advanced analytics to understand, predict, and optimize complex physical phenomena.
Added 6 hours ago
Data Engineer
S M Software Solutions Inc
Mississauga, ON
Full-time
We are seeking an experienced Data Engineer with strong expertise in Ab Initio Metadata Hub development, data lineage, metadata management, reference data development, data analytics,…
Added 6 hours ago
Data Engineer
S M Software Solutions Inc
Mississauga, ON
Full-time
We are seeking an experienced Data Engineer with strong expertise in Ab Initio Metadata Hub development, data lineage, metadata management, reference data development, data analytics,…
Added 6 hours ago
AI Engineer with Python - (Hybrid)
S M Software Solutions Inc
Mississauga, ON
Full-time
We are seeking an experienced AI Engineer with Python with 8+ years of software engineering experience and strong expertise in Python, FastAPI/Flask, AI/LLM applications, REST APIs, data…
Added 6 hours ago
AI Engineer
S M Software Solutions Inc
Mississauga, ON
Full-time
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Added 6 hours ago
AI Engineer with Python - (Hybrid)
S M Software Solutions Inc
Mississauga, ON
Full-time
We are seeking an experienced AI Engineer with Python with 8+ years of software engineering experience and strong expertise in Python, FastAPI/Flask, AI/LLM applications, REST APIs, data…
Added 6 hours ago
AI Engineer
S M Software Solutions Inc
Mississauga, ON
Full-time
We are seeking an experienced AI Engineer with 7+ years of experience in software and AI engineering to design, develop, and deploy AI/ML solutions. The ideal candidate will have strong…
Added 6 hours ago
AI Engineer
S M Software Solutions Inc
Mississauga, ON
Full-time
We are seeking an experienced AI Engineer with 7+ years of experience in software and AI engineering to design, develop, and deploy AI/ML solutions. The ideal candidate will have strong…
Added 6 hours ago
AI Engineer with Python - (Hybrid)
S M Software Solutions Inc
Mississauga, ON
Full-time
We are seeking an experienced AI Engineer with Python with 8+ years of software engineering experience and strong expertise in Python, FastAPI/Flask, AI/LLM applications, REST APIs, data…
Added 6 hours ago
Data Engineer
S M Software Solutions Inc
Mississauga, ON
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Added 7 hours ago
Staff AI Software Engineer
Qualcomm
Markham, ON
Full-time
…smarter, connected future for all. As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient…
Added 7 hours ago
Chemical Engineer
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Added 7 hours ago
Machine Learning Engineer - Early Career (Canada)
Jobright.ai
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…job search. They are seeking an Early Career Machine Learning Engineer to design, build, and maintain scalable infrastructure for AI agents, as well as optimize data processing and develop…
Added 7 hours ago
Machine Learning Engineer - Early Career (Canada)
Jobright.ai
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Full-time
…job search. They are seeking an Early Career Machine Learning Engineer to design, build, and maintain scalable infrastructure for AI agents, as well as optimize data processing and develop…
Added 7 hours ago
AI Engineer, Agent Product (Full-time/Part-time) (Canada)
Jobright.ai
Canada
Full-time · Part-time
Jobright is a rapidly growing AI job search platform in the U.S. that aims to simplify the job search process. The AI Engineer will be responsible for designing, building, and deploying AI…
Added 7 hours ago
AI Engineer, Mid Level
Jobright.ai
Canada
Full-time
…and helps users find better job outcomes. The Mid-Level AI Engineer designs, builds, evaluates, deploys, and operates machine learning and generative AI capabilities, including…
Added 7 hours ago
Prompt Engineer - Early Career (Canada)
Jobright.ai
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Full-time
…job search process. They are seeking an early-career Prompt Engineer to craft and evaluate prompts that enhance the performance of AI outputs across user-facing…
Added 7 hours ago
AI Engineer, Entry Level (Canada)
Jobright.ai
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Full-time
…the job search experience. They are seeking an entry-level AI Engineer to build and refine autonomous AI agents, develop sophisticated prompt engineering workflows, and integrate Large…

Propel Holdings

Analytics Engineer, Risk

Toronto, ON, M5E 1K3, Canada

Pay: $80,000 - $110,000
Job type: Full-time
Posting language: English
Posted: Sep 15, 2026

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Original job description

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 new 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 new 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

$80,000 - $110,000

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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More about this job

Responsibilities

The Analytics Engineer will design, build, and maintain ETL pipelines to deliver clean, production-ready data for credit risk models. They will also collaborate with data scientists to integrate new data sources and ensure the stability and quality of data infrastructure.

Requirements

Candidates must have a bachelor's degree in a quantitative field and at least 3 years of hands-on experience with Python and SQL. Proficiency in building data pipelines and familiarity with machine learning data lifecycles are essential for this role.

Skills

Python
SQL
ETL pipelines
Data engineering
Machine learning
Feature engineering
Data modeling
Git
Docker
Kubernetes
AWS
Data transformation
Time-series analysis
Credit risk
Data quality monitoring

Benefits

Competitive salary
Health benefits
Group health and dental benefits
Group RRSP program
Support for new parents

Visa sponsorship

Not detected in the job text

Keywords

Analytics Engineer
Fintech
Credit Risk
Python
SQL
ETL
Data Pipelines
Machine Learning
Pandas
NumPy
Scikit-learn
Neo4j
Docker
Kubernetes
AWS
S3
Data Drift
Feature Engineering
Git
CI/CD
Data Warehousing
Time-series
Tabular Data
Orchestration
Airflow
Metaflow
Dagster
Prefect
Data Infrastructure
Model Development

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