Data Engineer, Enterprise Data, Insights & Analytics – Canadian Tire – Toronto, ON
Location: Toronto, ON | Company: Canadian Tire
Canadian Tire has a full-time opening in Toronto for a Data Engineer, Enterprise Data, Insights & Analytics, a senior individual contributor role with a salary range of $80,000–$100,000. The position is posted against an existing vacancy within the organization.
You’ll design, build, and maintain scalable data pipelines that deliver accurate, timely financial and operational data for reporting, forecasting, and decision-making, working across Finance, Business, Analytics, and Technology teams.
About the Role: Data Engineer, Enterprise Data, Insights & Analytics
The day-to-day work centres on ETL/ELT pipeline development using Azure Synapse (Dedicated/Serverless Spark pools) and/or Databricks. You’ll extract, transform, and load financial and operational data into KPI data marts and reporting layers, and partner directly with business stakeholders to translate their requirements into production-ready solutions.
A significant part of the role involves data reconciliation and analytical validation across source systems, pipelines, and reporting outputs. You’ll investigate variances, conduct root-cause analysis, and resolve issues before data is released. Deadline-driven delivery is a feature of the work, particularly for time-sensitive financial datasets.
You’ll also design and implement data quality checks, monitoring frameworks, and control frameworks throughout the data lifecycle, execute QA testing in pre-production and production environments, and coordinate User Acceptance Testing (UAT) with business stakeholders through to formal sign-off.
Benefits and Salary
The broadband salary range is $80,000–$100,000. Final compensation depends on your experience, internal equity, industry benchmarks, and role-specific requirements; for critical roles, the offering is reviewed against market rate and conditions.
Canadian Tire offers comprehensive benefits and retirement programs, performance incentives, continuing education programs, career growth opportunities, and product discounts. The enhanced flex benefits program includes $5,000 per year in mental health benefits for benefits-eligible employees and their families, along with total well-being and mental health tools and resources. Canadian Tire Profit Sharing is also available to eligible employees.
Job Details
📌 Job Type: Full-time
🏢 Company: Canadian Tire
📍 Location: Toronto, ON
🆔 Requisition ID: JR166351
💰 Pay: $80,000–$100,000 per year
Responsibilities
The role covers the full data engineering lifecycle: pipeline development, data modelling, quality assurance, stakeholder collaboration, and documentation. You’ll own project-specific data transformations and logic while working with platform and infrastructure teams on Azure environments and deployment standards.
- Design, develop, and maintain ETL/ELT pipelines on Azure-based data platforms using Azure Synapse and/or Databricks to extract, transform, and load financial and operational data into KPI data marts and reporting layers.
- Partner with business stakeholders to gather and document requirements, understand financial processes, and translate them into scalable technical solutions.
- Build and maintain data models that support financial reporting, performance measurement, and downstream analysis, with thorough documentation.
- Support delivery of time-sensitive financial datasets, ensuring adherence to timelines, quality standards, and control requirements.
- Perform data reconciliation and analytical validation across source systems, pipelines, and reporting outputs; investigate variances, conduct root-cause analysis, and resolve issues prior to data release.
- Design and implement data quality checks, monitoring, and control frameworks to ensure accuracy, completeness, and reliability throughout the data lifecycle.
- Execute and validate QA testing in pre-production and production environments, ensuring changes meet functional, quality, and performance expectations.
- Coordinate User Acceptance Testing (UAT) with business stakeholders, support issue resolution, and obtain formal sign-off before production release.
- Create and maintain Metric Definition Documents (MDDs) to ensure consistent metric definitions across teams.
- Identify and implement automation and process improvements to reduce manual effort and improve scalability and reliability.
- Document data flows, transformations, reconciliation rules, and business definitions to support governance and transparency.
Requirements / Skills
The posting asks for a university degree in Computer Science, Engineering, Finance, Business, Mathematics, Statistics, or a related field, along with 2–4 years of experience in data engineering or analytics engineering supporting enterprise reporting. Several additional qualifications are listed as assets.
- Advanced SQL proficiency for data transformation, reconciliation, and validation (required).
- Python and Spark hands-on experience in Azure Synapse and/or Databricks environments, for data processing, automation, and quality checks (required).
- ETL/ELT workflow experience using Azure cloud-based data platforms (required).
- Data modelling and reporting-oriented design understanding, including KPI data marts (required).
- Data reconciliation experience: proven, hands-on track record investigating discrepancies across source systems, pipelines, and reporting layers, with root-cause analysis and fixes applied prior to data release (required).
- JIRA hands-on experience for story tracking, sprint execution, UAT coordination, and defect resolution (required).
- Git-based repositories such as Azure DevOps Repos (or similar) for code management and promotion across environments (required).
- Financial or operational reporting experience in enterprise environments (required).
- Power BI or Tableau dashboard development for financial or operational reporting (asset).
- Retail or Banking experience in finance, sales, inventory, operations, logistics, or related domains (asset).
How to Apply
Apply using the link below, which goes directly to the Canadian Tire careers site. Have your resume up to date and ready to upload before you begin.
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Job Summary & Tips for Applying
Quick Summary & What to Highlight: This Data Engineer, Enterprise Data, Insights & Analytics role at Canadian Tire in Toronto is a senior individual contributor position focused on building and maintaining financial and operational data pipelines on Azure. Two requirements to put front and centre on your resume: advanced SQL for data reconciliation and validation, which runs through almost every duty, and hands-on Python and Spark in Azure Synapse or Databricks, the core technical platform for this work.
Resume & Application Tips: The posting uses specific terminology worth mirroring on your resume: ETL/ELT pipelines, KPI data marts, Metric Definition Documents, and UAT coordination. If you’ve supported financial close cycles or deadline-driven reporting, call that out with the cadence and volume involved (for example, “delivered weekly financial datasets to six business units within a two-day SLA”). A line like “reduced manual reconciliation effort by 40% through automated data quality checks in Databricks” illustrates both the technical and business impact this posting emphasizes.
Interview Preparation: Prepare a concrete example of a data discrepancy you investigated end-to-end: the source, how you traced the root cause across pipeline stages, and what you put in place to prevent recurrence. Because the posting stresses deadline-driven financial datasets, be ready to describe a situation where you delivered under time pressure while maintaining data quality. Worth asking at interview: what the current deployment and promotion process looks like across Azure environments, and how QA testing is divided between the data engineering team and business stakeholders.
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