Data Engineer, Enterprise Data, Insights & Analytics

Canadian Tire; Toronto; On-site; CAD 80,000 - 100,000; Full time

Benefits offered by this job

Comprehensive benefits

Retirement programs

Profit sharing

Continuing education programs

Product discounts

Mental health benefits

Job summary

Canadian Tire in Toronto seeks a senior Data Engineer, Enterprise Data, Insights & Analytics to design, build, and maintain scalable data pipelines for financial and operational data. You will reconcile data, implement quality checks, and collaborate with Finance, Analytics, and Tech teams to deliver timely reporting and decision support.

Role requires 2–4 years in data engineering, proficiency in SQL, Python, Spark, and experience with Azure cloud platforms.

Qualifications

• University degree in computer science, engineering, finance, business, math, statistics, or related field.
• 2–4 years of experience in data or analytics engineering supporting enterprise reporting.
• Experience with SQL, Python and Spark in cloud data platforms (Azure Synapse/Databricks).
• Proven data reconciliation, validation, and discrepancy resolution in production data.

Responsibilities

• Develop and maintain ETL/ELT pipelines on Azure-based data platforms.
• Partner with stakeholders to gather requirements and translate them into solutions.
• Build data models to support financial reporting and KPI data marts.
• Ensure data quality, QA testing, and timely delivery of datasets.
• Conduct data reconciliation and root-cause analysis across systems.
• Implement data quality checks and governance across the lifecycle.
• Coordinate UAT with business stakeholders and obtain sign-off.

Skills

Advanced SQL

Python and Spark

ETL/ELT workflows

Data modelling

Data reconciliation

JIRA

Git-based repos

Financial reporting

Power BI/Tableau

Retail/Banking experience

Education

Bachelor's degree in CS/Engineering/Finance/Business/Math/Stats or related

Tools

Azure Synapse

Databricks

Azure DevOps Repos

Job description

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).

University degree in Computer Science, Engineering, Finance, Business, Mathematics, Statistics, or a related field. 2–4 years of experience in data engineering, analytics engineering, or related roles supporting enterprise reporting and analytics. Advanced SQL proficiency for data transformation, reconciliation, and validation. Hands‑on experience with Python and Spark in Azure Synapse and/or Databricks environments. Experience building ETL/ELT workflows using Azure cloud‑based data platforms. Understanding of data modeling and reporting‑oriented design (e.g., KPI data marts). Proven, hands‑on experience investigating data discrepancies across source systems, pipelines, and reporting layers, performing root‑cause analysis, and implementing fixes prior to data release. Hands‑on experience with JIRA for story tracking, sprint execution, UAT coordination, and defect resolution. Experience working with Git‑based repositories such as Azure DevOps Repos for code management. Experience supporting financial or operational reporting in enterprise environments. Experience building Power BI/Tableau dashboards for financial or operational reporting is an asset. Retail or Banking experience is an asset.