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Added 13 mins ago
Head of Security Centre
Geotab
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…large businesses to automate operations by integrating vehicle data with their other data assets. Processing billions of data points a day, Geotab leverages data analytics and machine…
Added 27 mins ago
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Senior Project Cost Specialist
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- Full-time
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Added 27 mins ago
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Assistant Warehouse and Distribution Manager
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…resources to work for you, is what has enabled Nippon Express to lead the world in innovative logistics…
Added 42 mins ago
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Manager, Digital Solutions
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Lead UX Developer (React)
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Added 57 mins ago
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Chief Information Officer
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Search Engine Optimization Manager
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- Full-time
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Added 1 hour ago
Senior Data Engineer
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AI Architect
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Added 1 hour ago
CT
Manager, Analytics Engineering
Canadian Tire Corporation
Toronto, ON
- Full-time
We are seeking a hands-on, strategic Manager, Analytics Engineering to lead the modernization of enterprise data platforms from Hadoop to Microsoft Azure. A core mandate is to build…
Added 1 hour ago
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Canadian Tire Corporation

Manager, Analytics Engineering

Toronto, ON, Canada

Full-time

Apply About employer

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Job details

Job type: Full-time
Apply by: Nov 13, 2026
Posting language: English
Posted: Oct 30, 2026

Original job description

What you’ll do :

We are seeking a hands-on, strategic Manager, Analytics Engineering to lead the modernization of enterprise data platforms from Hadoop to Microsoft Azure. A core mandate is to build reusable, AI-enabled frameworks that make migration, data engineering, and workload optimization as efficient and accurate as possible. This role will combine intelligent automation with rigorous validation to improve delivery speed, data quality, reliability, scalability, and cost efficiency.

The successful candidate will combine technical depth with strong people leadership and program execution. They will partner with architecture, analytics, security, infrastructure, and business teams to establish AI-enabled engineering and migration patterns, manage delivery risks, and build a sustainable Azure data platform. Frameworks must include measurable quality controls, traceability, and human review where needed to validate AI-generated outputs and manage exceptions.

Key Responsibilities

Hadoop-to-Azure Migration

Lead the end-to-end migration of data, pipelines, and workloads from Hadoop environments to Azure.

Define migration waves, priorities, dependencies, acceptance criteria, cutover plans, and rollback strategies.

Assess existing Hadoop jobs, datasets, integrations, and technical debt to determine whether workloads should be rehosted, refactored, rebuilt, retired, or consolidated.

Build reusable, AI-enabled migration frameworks to accelerate workload assessment, code conversion, test generation, and documentation, with automated reconciliation and human approval for production cutovers.

Coordinate data validation, parallel runs, production cutovers, decommissioning, and post-migration stabilization.

Data Engineering

Lead the design and delivery of secure, scalable, and maintainable batch and streaming data pipelines on Azure.

Build and maintain reusable, AI-enabled data engineering frameworks for pipeline development, code generation, automated testing, data-quality checks, and documentation; establish standards for source control, CI/CD, observability, and lineage.

Guide teams in designing reliable data models and curated data products that support analytics, reporting, and advanced use cases.

Partner with IT, architecture, governance, privacy, and security teams to embed controls throughout the data lifecycle, including approved AI tools, protection of sensitive data, traceability of AI-generated changes, and risk-based human review.

Workload and Job Optimization

Develop AI-assisted optimization frameworks to identify bottlenecks, recommend improvements, and automate repeatable tuning tasks; validate recommendations against runtime, throughput, accuracy, stability, resource utilization, and cloud-cost baselines.

Identify inefficient queries, data skew, partitioning issues, orchestration bottlenecks, unnecessary data movement, and failed-job patterns.

Establish performance baselines, service-level objectives, monitoring, alerting, capacity plans, and cost-management practices; measure framework effectiveness through delivery time, manual effort, data accuracy, defect rates, and processing cost.

Prioritize optimization opportunities using measurable business value, risk reduction, and total cost of ownership.

People Leadership and Delivery

Lead, coach, and develop data engineers and technical leads, building capability in responsible AI-assisted engineering and driving adoption of reusable frameworks, accountability, collaboration, and continuous improvement.

Translate the modernization strategy into clear roadmaps, delivery plans, resource needs, and team objectives.

Manage delivery across internal teams and external partners, proactively addressing scope, schedule, quality, risk, and dependencies.

Communicate technical decisions, migration progress, trade-offs, and outcomes to both technical and executive audiences.

What you bring:-

Progressive experience in data engineering, data-platform modernization, or cloud migration, including experience leading technical teams.

Demonstrated experience migrating Hadoop-based data and workloads to Microsoft Azure.

Strong knowledge of distributed data processing, data pipelines, orchestration, data modelling, storage patterns, and production operations.

Experience with relevant Azure data services and modern engineering practices, including building reusable AI-enabled frameworks for migration, pipeline development, testing, and optimization, with demonstrated ability to validate outputs and measure efficiency and accuracy gains.

Proven ability to tune data jobs, troubleshoot complex performance issues, and improve reliability and cloud cost efficiency.

Working knowledge of data governance, security, privacy, access controls, metadata, lineage, retention, and audit requirements.

Strong stakeholder management, communication, prioritization, and change-leadership skills.

Bachelor’s degree in computer science, engineering, information systems, or a related discipline, or equivalent practical experience.

We’re always looking for great talent! In addition to competitive pay, we offer:

Career growth opportunities and product discounts

Broadband Salary Range: $79,000.00 - 131,000.00 CAD Annual

Our typical hiring range is between $90,000.00 - 130,000.00 CAD per annum. Salary decisions are also dependent on other factors such as your experience, job-related knowledge, skills and competencies, market location, industry benchmarks, internal equity and other role-specific requirements

This posting represents an existing vacancy within our organization.

We may use artificial intelligence tools as part of our recruitment process to assist in the initial screening of resumes. All hiring decisions, including candidate evaluation, selection, and disposition, are made by human recruiters.

About Us

Canadian Tire Corporation, Limited (“CTC”) is one of Canada’s most admired and trusted companies. With more than 90 Owned Brands, over 1,600 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.

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.

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More about this job

Responsibilities

Lead the end-to-end migration of enterprise data platforms from Hadoop to Microsoft Azure while building AI-enabled frameworks for engineering and optimization. Manage delivery roadmaps, coach technical teams, and partner with cross-functional stakeholders to ensure scalable, secure, and cost-efficient data solutions.

Requirements

Requires progressive experience in data engineering, cloud migration, and technical team leadership, specifically with Hadoop-to-Azure transitions. Candidates must possess strong knowledge of distributed data processing, data modeling, and modern engineering practices alongside a relevant bachelor's degree.

Skills

Data engineering
Cloud migration
Microsoft Azure
Hadoop
Data pipelines
AI-enabled frameworks
Data modeling
Performance tuning
Data governance
CI/CD
Leadership
Stakeholder management
Automation
Data quality
Cloud cost management
Strategic planning

Benefits

Career growth opportunities
Product discounts
Profit sharing
Retirement and savings programs
Flex benefits program
Mental health benefits
Supported learning

Visa sponsorship

Not detected in the job text

Keywords

Analytics Engineering
Hadoop
Microsoft Azure
Data Migration
AI-enabled frameworks
Data Engineering
Cloud Modernization
CI/CD
Data Pipelines
Performance Tuning
Data Governance
Data Modeling
Automation
Scalability
Cloud Cost Management
Technical Leadership
Stakeholder Management
Batch Processing
Streaming Data
Observability
Data Lineage
Security
Privacy
Technical Debt
Workload Optimization
Service-level objectives
Capacity Planning
Strategic Planning
Enterprise Data Platforms
Cloud Migration

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