Job Title: Data Engineer, AI and Advanced Analytics
Location: Toronto, ON (Onsite)
Estimated Duration: Fulltime
About Us
Canadian Tire Corporation, Limited (“CTC”) is one of Canada’s most admired and trusted companies. With more than 90 Owned Brands, 1,700 retail locations, financial services, exemplary e-commerce capabilities, and exciting market-leading merchandising strategies. We dream big and work as one to innovate with purpose for our customers at every level of our business, investing in new technologies and products, and doubling down on top talent to drive the company forward. We offer competitive salaries and wages to CTC employees, as well as store discounts, supported learning through our Triangle Learning Academy, Canadian Tire Profit Sharing, and retirement and savings programs for eligible employees. As part of our enhanced flex benefits program, we offer mental health benefits in the amount of $5,000 per year for benefits-eligible employees and their families, including total well-being, and mental health tools and resources for all employees. Join us in helping to make life in Canada better through living and working our Core Values: we are innovators and entrepreneurs at our core, outcomes drive us, inclusion is a must, we are stronger together and we take personal responsibility. It is an especially exciting time to join CTC and its family of companies where career opportunities are wide-ranging! Join us, where there's a place for you here.
We are seeking a skilled and experienced Data Engineer to join the Canadian Tire Corporation. Your primary focus will be on ensuring the stability, reliability, and performance of ML models in production environments. Working closely with data scientists, and IT teams, you will deploy and manage ML models, monitor their performance, develop robust monitoring systems, and automate processes for continuous evaluation. Your expertise in machine learning (ML) model Productionisation, model deployment, and automation will be crucial in driving operational excellence and delivering impactful AI solutions.
What You’ll Do
- Design, develop, and manage ETL data pipelines that facilitate the detailed extraction, transformation, and loading of data from diverse sources.
- Responsible for designing and executing robust data quality checks, along with implementation and maintenance of a curated feature store.
- Deploy and scale existing machine learning models in production, ensuring robust data ingestion, update and model scoring.
- Collaborate closely with data scientists to provide clean, well-structured data for modelling and scale and automate experimental models for production use.
- Work with external data engineering teams for infrastructure setup and database management but handles project-specific data needs internally.
- Collaborates with external teams to ensure infrastructure aligns with deployment but owns the ML model lifecycle internally.
What You Bring
- Master’s degree in computer science, software engineering or an equally technical field.
- 2+ years of previous data engineering experience with Azure-related data technologies.
- Proven experience in deploying and managing AI models in production environments
- Hands-on knowledge of Azure Databricks, Azure Data Factory, Azure Data Lake Storage, Synapse Serverless/dedicated/spark pools, Python, PySpark, and MLflow, along with experience crafting and developing scripts for ETL processes and automation in Azure Data Factory and Azure Databricks.
- Solid understanding of model performance metrics and evaluation techniques.
- Proficiency in programming languages commonly used in ML development such as Python and R.
- Experience with model deployment frameworks (e.g., TensorFlow Serving), containerization (e.g., Kubernetes, Docker), and cloud platforms (e.g., Azure).
- Familiarity with DevOps practices and tools for CI/CD pipelines (e.g., GitLab, Jenkins) in the context of deploying AI models.
- Understanding of Azure infrastructure, including subscriptions, resource groups, resources, access control with role-based access control, integrations with Azure AD, and Azure security principles (user group, service principal, managed identity), password/credential/key management, and data protection.
- Excellent problem-solving skills with a focus on root cause analysis and continuous improvement.
- Excellent oral and written communication skills, with the ability to communicate both technical and business concepts, as well as strong presentation skills.
- Adaptability and willingness to learn new things and stay on top of the new deployment and ETL updates.
- Ability to lead technical presentations, demonstrations, workshops, design sessions, proofs of concept, and pilots.
Preferred Qualifications:
- Experience with data modelling, data mart, data lakehouse architecture, SCD, data mesh, and delta lake overall.
- Knowledge of distributed computing frameworks (e.g., Apache Spark) for large-scale data processing.
- Experience with deep learning frameworks (e.g., PyTorch) and custom made DNN solutions
Our Commitment to Diversity, Inclusion and Belonging
We are committed to fostering an environment where belonging thrives, and diversity, inclusion and equity are infused into everything we do. We believe in building an organizational culture where people are consistently treated with dignity while respecting individual religion, nationality, gender, race, age, perceived ability, spoken language, sexual orientation, and identification. We are united in our purpose of being here to help make life in Canada better.
Accommodations
We stand firm in our Core Value that inclusion is a must. We welcome and encourage candidates from equity-seeking groups such as people who identify as racialized, Indigenous, 2SLGBTQIA+, women, people with disabilities, and beyond. Should you require any accommodation in applying for this role, or throughout the interview process, please make them known when contacted and we will work with you to help meet your needs.