Manager, Analytics Engineering

Role overview

Hadoop-to-Azure migration

• Lead end-to-end migration of data, pipelines, and workloads from Hadoop to Azure; define waves, dependencies, acceptance criteria, cutover, and rollback plans.
• Assess jobs, datasets, integrations, and technical debt to determine whether workloads should be rehosted, refactored, rebuilt, retired, or consolidated.
• Build AI-enabled migration frameworks for assessment, conversion, test generation, and documentation, with automated reconciliation and human approval for production cutovers.
• Coordinate validation, parallel runs, cutovers, decommissioning, and post-migration stabilization.

Data engineering and controls

• Lead secure, scalable batch and streaming pipelines on Azure and guide design of reliable data models and curated data products.
• Build reusable AI-enabled frameworks for pipeline development, code generation, testing, data-quality checks, and documentation; set source control, CI/CD, observability, and lineage standards.
• Work with IT, architecture, governance, privacy, and security to embed lifecycle controls, approved AI tools, sensitive-data protection, change traceability, and risk-based human review.

Optimization and leadership

• Develop AI-assisted optimization, validate against runtime, throughput, accuracy, stability, resource, and cost baselines, and address queries, skew, partitioning, orchestration, data movement, and failed jobs.
• Establish performance baselines, service-level objectives, monitoring, alerting, capacity plans, and cost practices; measure delivery time, effort, accuracy, defects, and processing cost.
• Lead and develop data engineers and technical leads; turn strategy into roadmaps, plans, resource needs, and team objectives.
• Manage internal and partner delivery, address scope, schedule, quality, risk, and dependencies, and communicate progress, decisions, trade-offs, and outcomes to technical and executive audiences.

Qualifications

• Progressive experience in data engineering, data-platform modernization, or cloud migration, including leading technical teams.
• Demonstrated experience migrating Hadoop data and workloads to Microsoft Azure.
• Strong knowledge of distributed data processing, pipelines, orchestration, data modeling, storage patterns, and production operations.
• Experience with Azure data services and modern engineering practices, including reusable AI-enabled frameworks for migration, pipeline development, testing, and optimization.
• Ability to validate AI-generated outputs, measure gains, tune data jobs, troubleshoot performance issues, and improve reliability and cloud cost efficiency.
• Working knowledge of 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.

Compensation

• The stated broadband salary range is CAD 79,000 to CAD 131,000 annually; the typical hiring range is CAD 90,000 to CAD 130,000 per annum.
• Salary decisions depend on experience, job-related knowledge, skills, competencies, market location, benchmarks, internal equity, and role-specific factors.

Benefits

• The posting mentions career growth, product discounts, competitive compensation, retirement and savings programs, profit sharing, learning support, and mental health benefits for eligible employees.

About Canadian Tire Corporation