Data Engineer I

Loblaw Companies Limited•Brampton, ON

1d•CA$68,000 - CA$93,500•Onsite

About The Position

Loblaw Technology & Analytics is looking for a Data Engineer to join our dynamic team. In this role, you'll help design, build, and maintain scalable data pipelines and reporting solutions that support critical business operations and decision-making. Working on a diverse portfolio of projects, you'll collaborate with a talented team to deliver innovative, reliable data solutions that drive meaningful business impact.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Data Engineering, Information Technology, Computer Engineering, Mathematics, or a related technical field, or an equivalent combination of education and practical experience.
Experience with cloud technologies (preferably Google Cloud Platform), SQL, Python, git, CI/CD and ETL/data pipeline development through academic projects, internships, or professional experience.
Blend of both Development and SRE mindset (i.e. software and infrastructure)
Proven experience with the principles of ITIL Incident Management, Problem Management and Change Management

Nice To Haves

Relevant cloud or data engineering certifications (e.g., Google Cloud Professional Data Engineer, Associate Cloud Engineer) and exposure to AI/ML technologies, generative AI, or cloud-based AI services are considered an asset.

Responsibilities

Design, build, and optimize scalable ETL processes, data pipelines, and cloud-based solutions to support reliable data integration, reporting, and business insights.
Collaborate with cross-functional teams, including data specialists, developers, infrastructure, security, and business stakeholders, to design, implement, and deliver innovative data solutions.
Ensure high-quality, reliable solutions by performing code reviews, implementing testing and automation, improving code quality, and supporting successful production releases and deployments.
Drive continuous improvement and innovation by identifying opportunities to leverage Google Cloud Platform (GCP), automating processes, contributing to architectural design, and evaluating new technologies through proofs of concept.
Monitor, troubleshoot, and resolve application, pipeline, and infrastructure issues by identifying root causes, recommending solutions, and continuously improving system performance and reliability.