Principal Software Engineer - Data and AI Platforms

About the Company

About the Enterprise Data and AI Team

Core Responsibilities

• Own the design and implementation of the enterprise data platform and reliable, governed data products and services.
• Build enterprise-grade data products, semantic layers, and enterprise data models for multiple teams and business domains.
• Set platform direction, engineering standards, and technical practices while serving as the definitive technical authority.
• Partner with product, business, technology, and VP-level stakeholders on technical strategy, roadmap, and cross-functional initiatives.
• Provide on-call support outside standard business hours when required.

Selected Responsibilities

• Define the vision and approach for enterprise data initiatives and deliver technology solution designs.
• Write high-quality production code to solve complex technical challenges when hands-on expertise is needed.
• Collaborate with architects on system design, implementation feasibility, and operational implications.
• Challenge existing architecture decisions and propose solutions based on system design expertise.
• Advise executives on build-versus-buy decisions, technology selection, and implementation risks.
• Drive engineering practices, workflow improvements, tooling enhancements, and systemic blocker removal across teams.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Information Technology, or equivalent experience; a master's degree is preferred.
• 11-15 years of progressive software engineering experience in large-scale system design, technical architecture, and cross-functional leadership.
• Expert-level coding ability across multiple languages and frameworks with production software experience.
• Experience with complex system analysis, technical trade-offs, implementation planning, and cross-organizational technology programs.
• End-to-end ownership of enterprise data lake architecture, including ingestion, orchestration, DataOps, reliability, security, privacy, and access control.
• Experience with shared data APIs, platform services, semantic layers, canonical models, taxonomies, ontologies, or knowledge graphs.
• Exposure to AI-driven systems, knowledge representation for LLM applications, and retail or similarly complex consumer data platforms.
• Authorization to work in Canada is required.

Values

Compensation

• The typical hiring range is CAD 196,600 to CAD 258,100 annually.
• Permanent employees may be eligible for annual bonuses and equity offerings subject to program eligibility.

Benefits

• Benefits may include health and dental coverage, mental health plans, paid time off, retirement plan matching, employee discounts, fitness and yoga classes, parenthood top-up, development courses, mentorship, and leadership programs.

Workplace Arrangement

• The role is hybrid, with in-person collaboration and work performed onsite a minimum of four days per week.