Solution Architect Data and AI

Being part of Air Canada is to become part of an iconic Canadian symbol, recently ranked the best Airline in North America. Let your career take flight by joining our diverse and vibrant team at the leading edge of passenger aviation.

As a Data & AI Solution Architect, you will provide strategic technical leadership in the design, evolution, and governance of enterprise-wide Artificial Intelligence, Data Engineering, Analytics, and Data Platform solutions. This senior role influences long-term technology direction, ensures architectural coherence across the organization, and drives adoption of scalable, secure, and innovative data and AI capabilities.
You will be responsible for the translation of business strategies and requirements into specific technical solutions, applications and process designs. You play an integral role in the solution definition and you assume the overall responsibility for all technical aspects of solution delivery, from inception through design to implementation (including all solution aspects related to development, infrastructure, data and configuration management perspectives).

Responsibilities:

• Define and evolve enterprise architecture standards, reference architectures, and patterns for AI, Data, Operational Analytics, and cloud-native platforms.
• Lead enterprise-scale solution design, ensuring alignment with business strategy, technology roadmaps, and regulatory requirements.
• Oversee end-to-end solution architecture for complex programs, guiding teams through inception, conceptual architecture, detailed design, and implementation.
• Define and govern enterprise BI and analytics consumption architecture, including semantic layers, metrics frameworks, and reporting patterns to ensure consistency, scalability, and reuse across business domains.
• Serve as a senior technical advisor to executives, product owners, and engineering leaders.
• Lead evaluation and selection of emerging technologies, platforms, and tools across LLMs, Agentic AI, AI/ML/Optimization, Data Engineering, BI, LLMOps/MLOps, and DataOps.
• Provide advanced architectural oversight for data platforms such as Data Lakes, EDW, ODS, streaming architectures, and event-driven systems.
• Design scalable enterprise data models and AI solution frameworks that support predictive analytics, real-time intelligence, and automation.
• Establish architecture governance processes including technical review boards, design approvals, and compliance validation.
• Mentor solution architects, data engineers, and AI practitioners; elevate architectural maturity across teams.
• Drive modernization initiatives including migration to cloud-native platforms, container orchestration (Kubernetes), and serverless architectures.
• Direct enterprise security and data governance alignment, including encryption, IAM/RBAC, data classification, lineage, and privacy controls.
• Create executive-level architecture artifacts, roadmaps, capability maps, and investment recommendations.
• Provide architectural leadership to development teams, and serve as the primary architect resource, and provide technical guidance and leadership to all internal and external teams involved in the implementation process.
• Create solution architecture documents that describe and explain solutions attributes and associated benefits and maintain documentation in collaboration with enterprise architects as well as others solution architects.
• Support the identification of opportunities for continuous improvement of solution management methodologies, including obtaining feedback after the solution has been -implemented.
• Build standard solution templates for different business use cases.
• Drive optimization on performance and cost by guiding modeling strategies, aggregation approaches, caching, and usage patterns.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).
• 10+ years of IT experience, including 5+ years as a solution or enterprise architect.
• Expertise in cloud architectures (Azure preferred; AWS/GCP beneficial).
• Deep experience designing large-scale data ecosystems including Data Lakehouse, streaming frameworks, and enterprise data warehouses.
• Strong knowledge of big data processing (Spark, Hadoop), distributed systems, and modern data engineering practices.
• Expert-level SQL and strong programming skills (Python, Scala, or Java).
• Advanced experience with ETL/ELT frameworks (Databricks, ADF, DBT and others).
• Strong background in AI/ML platforms, MLOps, model lifecycle management, and engineering best practices.
• Experience implementing DevOps/DataOps pipelines, automation frameworks, and CI/CD for data and AI workloads.
• Knowledge of enterprise modeling languages (UML, ArchiMate); LeanX, Sparx EA experience an asset.
• Knowledge of Dimensional Data Modelling, Data marts, Data Vault 2.0 modeling.
• Knowledge of Master Data and Reference Data concepts and solutions
• Knowledge of Big Data concepts, Cloud Solutions such as Azure, AWS or GCP.
• Good knowledge of Data Governance principles & tools such as Collibra.
• Strong analytical, decision-making skills and demonstrated ability to learn new tools and systems.
• Knowledge in APIs, web services concepts, standards and JSON, XML, XML Schema.
• Experience in designing and implementing large server software with particular attention to security, scalability, and high performance.
• Ability to work across multiple technical teams to set direction and priority.
• Ability to work independently and as part of a team while demonstrating initiative and using good business acumen.
• Ability to motivate and integrate team members, Team player with effective interpersonal skills.
• Experience working within multidisciplinary and collaborative environments.
• Demonstrate punctuality and dependability to support overall team success in a fast-paced environment.

Preferred Certifications

• TOGAF or equivalent enterprise architecture framework
• Cloud certifications (Azure Solutions Architect Expert preferred)
• DAMA/DCP Certifications
• Machine Learning / Deep Learning certifications
• Agentic AI

Conditions of Employment:

Candidates must be eligible to work in the country of interest at the time any offer of employment is made and are responsible for obtaining any required work permits, visas, or other authorizations necessary for employment. Prior to their start date, candidates will also need to provide proof of their eligibility to work in the country of interest.

Linguistic Requirements

Based on equal qualifications, preference will be given to bilingual candidates.

Diversity and Inclusion

Air Canada is strongly committed to Diversity and Inclusion and aims to create a healthy, accessible and rewarding work environment which highlights employees’ unique contributions to our company’s success.

As an equal opportunity employer, we welcome applications from all to help us build a diverse workforce which reflects the diversity of our customers, and communities, in which we live and serve.

Air Canada thanks all candidates for their interest; however only those selected to continue in the process will be contacted.