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Air Canada is seeking a technically experienced Specialist, Data & AI primarily focusing on DevOps to define, build, and operate the internal platform capabilities that enable Data & AI teams to deliver analytics, data products, and AI solutions reliably, efficiently, and securely. This role is responsible for driving platform engineering practices across CI/CD, automation, environment governance, observability, and operational excellence, and for partnering with engineering and architecture stakeholders to shape the platform’s technical roadmap and implementation standards.

The Specialist works with a high degree of autonomy, leads complex initiatives spanning multiple environments and teams, and serves as a technical mentor and escalation point for platform delivery and operational issues. The role requires strong engineering judgment, an automation-first mindset, demonstrated ability to execute with quality, accuracy, and security and the ability to innovate when the situation demands.

In addition to the DevOps primary focus, the Specialist provides secondary support across data engineering, data quality, and data science activities when platform workload permits.

This position reports to the Manager, Data & AI within the Data Platforms department.

Responsibilities:

1) Platform Strategy, Standards & Engineering Enablement

• Help define and evolve the target-state Data & AI platform delivery model (DevOps/SRE practices, release governance, environment strategy, and automation standards).
• Establish and continuously improve platform templates, standards, guidelines, and procedures, recommending adjustments based on results and operational learnings.
• Ensure data engineering and AI enablement initiatives are properly supported at the infrastructure and architecture levels (reliability, security, scalability, and maintainability).

2) CI/CD, Release Engineering & Environment Governance (Ownership)

• Design, implement, and maintain CI/CD pipelines and automated release frameworks for multiple data platform components and products (build, test, security scans, deployment approvals, promotion strategies).
• Own branching/merging and release strategies, maintaining code branches and integrations across multiple branches and teams.
• Lead and coordinate go-live activities including PR review and approvals and supporting the release deployment as and when needed.

3) Platform Tooling, Automation & Developer Experience

• Build and enhance reusable platform capabilities: scripts, automation components, and internal tooling that improves developer velocity and operational consistency.
• Configure and support complex installations and integrations; quickly resolve defects or automation/script issues found during deployments and operations.
• Apply sound Agile engineering practices (code reviews, testing, automation) to deliver high-quality platform changes and reduce operational risk.

4) Platform Operations, Reliability & Incident Response (SRE mindset)

• Provide day-to-day operational support and technical expertise to technical and non-technical teams; act as an escalation point for platform incidents and release issues.
• Implement and improve monitoring, logging, alerting, and reliability practices, leveraging tooling for deployment, monitoring, and site reliability.
• Perform structured root cause analysis across systems, pipelines, and processes; drive corrective/preventive actions and measurable reliability improvements.

5) Security, Compliance, and Controls by Design

• Maintain platform security measures through implementation of technology plans, policies, and standards; ensure access control, auditability, and compliance requirements are met.
• Embed security into delivery pipelines (secrets management, least privilege, dependency hygiene, and environment controls) and validate that automation is supportable and compliant.

6) Cross-functional Delivery Leadership & Stakeholder Partnership

• Collaborate closely with architects, quality teams, and delivery stakeholders to ensure timely delivery of projects, features, bug fixes, and infrastructure improvements into multiple production environments.
• Partner with Data & AI stakeholders (Solution Architects, Data Engineers, Data Scientists, Analysts, Tech Leads, Product Owners/Managers, and Platform Developers) to remove delivery constraints and unblock deployments.
• Contribute to KPI development and continuous improvement to track delivery efficiency, quality, and operational health.

7) Mentorship & Capability Building (Senior expectation)

• Coach and mentor junior platform developers on DevOps best practices, automation patterns, and engineering quality; raise the baseline maturity of the platform team.

8) Secondary Responsibilities — Data Engineering, Data Quality & Data Science Support

• Support the design and build-out of data models and the mapping of structured and unstructured data sources to those models when platform workload permits.
• Contribute to the engineering of scalable ETL/ELT pipelines and the codification of business rules supporting data integration into the data lake and data warehouse.
• Assist in the development and integration of data quality solutions (profiling, validation, monitoring) into platform pipelines.
• Support BI/web app development (e.g., Streamlit) and the build-out of cutting-edge Generative AI / LLM-based applications as required.
• Continuously evaluate emerging data, analytics, and AI technologies and recommend enhancements to the team’s capabilities.
• Maintain and update technical documentation, procedures, and supporting database/model configurations aligned with organizational requirements.

Qualifications

Required

• A degree in Computer Science, a relevant technical certification, and/or equivalent experience commensurate with the role.
• 5+ years of experience in DevOps / platform engineering / cloud engineering with progressively increasing responsibility and demonstrated mastery of DevOps quality and control processes.
• Strong scripting and automation skills (e.g., Python) and demonstrated ability to implement reliable automation at scale.
• Advanced working knowledge of SQL and experience with data warehouse concepts and platforms.
• Working knowledge of Streamlit and LLM technologies.
• Strong experience with version control and branching strategies (e.g., Git).
• Experience with cloud computing platforms (e.g., Microsoft Azure/AWS/GCP) and cloud-based monitoring/logging; familiarity with cost analysis tooling is an asset.
• Knowledge of deployment, monitoring, and site reliability tooling and practices.
• Strong communication skills with the ability to interface effectively with peers, stakeholders, and leadership in a fast-paced environment.
• Team player with the ability to function effectively in a fast-paced, team-oriented work environment with a bias toward action.
• Ability to understand and influence decisions strategically in the interest of Air Canada first and foremost.
• Demonstrate punctuality and dependability to support overall team success in a fast-paced environment.

Preferred / Assets

• Experience with containerization tools (e.g., Docker) and understanding of network topologies/protocols.
• API development experience.
• Familiarity with data platforms and tooling such as Snowflake, Databricks, Talend, Azure Data Factory.
• Working knowledge of Collibra Data Governance is an asset.
• Experience using AI-assisted coding tools (e.g., Cursor, GitHub Copilot, Claude Code) is an asset.

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.