Data and AI Analyst

About Air Canada

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.

The Data & AI Analyst will be responsible for supporting the technical aspects of data projects and business projects that have a data component and establishing and documenting technical standards and best practices. This role is responsible for documenting, delivering, and maintaining data specifications and practice of applications following the introduction of new projects. This is to be accomplished by adhering to Air Canada’s architecture, business requirements, templates, and standards to ensure a high-quality analysis is maintained throughout. The incumbent will constantly update the practices to enhance the evolution of our data ecosystem.

This position will be reporting to the Manager, Data Product Management.

Responsibilities

• Review the Data Requirement Document to ensure data requirements are clear and detailed.
• Understand and clarify both functional (FR) and non-functional (NFR) requirements (Data specific).
• Evaluate the data requirements for user stories and gather the necessary data points.
• Review the Data Ingestion Specification to confirm that the source data meets all essential criteria.
• Develop innovative and effective approaches to solve business problems through data analytics approaches and communicate results and methodologies.
• Conduct preliminary data analysis and identify critical data gaps or risks whenever possible. Provide analysis result and clearly document risks, assumptions, etc.
• Provide the appropriate data mapping for the ETL specifications (STTM) and a centralized data lineage document for all data assets.
• Collaboratively participate in the development of data models by working in close partnership with the designated data modeler. Together, ensure that models align with data requirements and support intended analytical outcomes.
• Jointly provide and receive insights, constructive feedback, and clarification on requirements, data sources, data quality, business context, and any technical constraints—fostering a shared responsibility for delivering robust, actionable data solutions.
• Perform a comprehensive evaluation, grant approvals for STTM documents and ensure data governance is implemented (data dictionary and PI identification).
• Advise on test case recommendations and provide recommendations for development validation processes.
• Initiate data analysis and identify opportunities that creates a positive impact on business.
• Work Closely with the other data analysts within the team regarding the current processes, frameworks, and AC standards.
• Work closely with relevant stakeholders and product managers to collect and use information for improved business and operational performance.
• Responsible for actively supporting the development and enhancement of processes, best practices of the data analysis community of practices.

Qualifications

• A relevant University degree/technical certification, and relevant experience commensurate to the role.
• 3-5 years of data analytics experience in a large company and experience in guiding a technical team.
• Experience on cloud solutions (AWS, Azzure…), data vault approach and Datawarehouse (Snowflake).
• Experience with the following technologies Databricks, Snowflake, ADF and Talend.
• Proficiency in at least one modern programming language such as Python, SQL for querying databases.
• Deep understanding of big data challenges and ecosystems.
• Ability to work effectively under pressure and in rapidly changing environments or uncertain conditions.
• Ability to act as a mentor for a data analysts’ team, facing architects, data modelers, and the different IT and business stakeholders.
• Ability and willingness to learn new tools and technologies.
• Capable of solving complex problems by using a logical, systematic, and sequential approach.
• Takes responsibility for the results and future direction of the organization.
• Comfortable working both as part of a high-performing, diverse team and as an independent performer.
• Able to approach a problem by using a logical, systematic, sequential approach.
• Demonstrate punctuality and dependability to support overall team success in a fast-paced environment.

Key skills/competency

• Data Analytics
• Cloud Solutions (AWS, Azure)
• Data Warehousing (Snowflake)
• Python & SQL
• ETL & Data Mapping
• Data Governance
• Data Modeling
• Big Data Ecosystems
• Stakeholder Collaboration
• Mentorship & Leadership