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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. Join Air Canada—an iconic Canadian brand and North America’s top-ranked airline—as we lead the next wave of digital transformation in aviation. With major IT initiatives underway and a strong commitment to innovation, this is a unique opportunity to help shape the future of travel technology. We’re looking for a highly skilled and experienced Data Engineering Technical Analyst to drive the design, development, and delivery of scalable data solutions. This role involves leading technical assessments, mentoring data engineers, and actively developing and reviewing data pipelines to ensure robustness, scalability, and performance across enterprise data platforms. The ideal candidate will possess deep expertise in cloud-based data engineering, DevOps practices, and modern data architecture, with a strong focus on Azure and Snowflake ecosystems. As a champion of technical excellence, the Technical Analyst contributes to a culture of innovation, collaboration, and continuous improvement. You’ll work closely with architects, developers, and product teams to enhance operational efficiency, ensure platform stability, and explore emerging technologies—including AI and data-driven insights—that help keep our airline systems modern, scalable, and customer-focused. Let your career take flight by joining a team that’s redefining the digital passenger experience at the forefront of global aviation.
Job Responsibility
Manage implementation of solutions for exploratory data analysis and conducts implementation assessments based on Architecture Overview Documents (AOD) and Detailed Data Solutions
Provide accurate effort estimations and assess feasibility of proposed architectures and data models
Design and develop cost-effective, scalable ELT pipelines using reusable components and frameworks
Document pipeline implementation approach including scheduling, dependencies, error handling, monitoring, and alerting
Monitor and resolve alerts/failures in prod/non-prod environments
Review and approve pipelines developed by data engineers
Set up non-production and production environments including MFT flows, database/schema configurations, RBAC, cloud services, Git repositories, and defining appropriate branching strategies
Collaborate with stakeholders on UAT and production release strategies
Mentor and guide data engineers on best practices, business logic implementation, and quality assurance
Scramble and generate mock data for testing purposes
Identify and document technical debt
differentiate between defects and scope changes and effectively communicate with product team
Lead deployment and transition-to-operations (TTO) activities for UAT and production
Apply strong understanding of DevOps processes, Star Schema, Data Vault, and data warehousing principles
Requirements
3-5 years of experience leading enterprise data warehouse development teams
Proven success in Agile environments and cloud-based data platforms, especially Azure and Snowflake
Expertise in building robust, scalable data pipelines for batch and streaming data
Proficiency in SQL, Python, stored procedures, and scheduling tools
Hands-on experience with ETL/ELT tools such as Azure Data Factory (ADF), Databricks, Snowflake, DBT and Talend
Skilled in implementing monitoring and alerting mechanisms for data pipelines
Strong capability in reviewing engineering deliverables for performance, scalability, and maintainability
Experience with prompt engineering and leveraging Generative AI (GenAI) to accelerate development and automate engineering workflows
Bachelor's degree in Engineering, Computer Science, Mathematics, or a related field
Excellent communication, problem-solving, and analytical skills
Proven leadership and mentoring capabilities
Strong collaboration skills with cross-functional teams
Demonstrate punctuality and dependability to support overall team success in a fast-paced environment
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
Based on equal qualifications, preference will be given to bilingual candidates