Tech Analyst Data & AI - Temporary

Overview

Air Canada, an iconic Canadian brand and North America’s top-ranked airline, is leading the digital transformation in aviation. The Tech Analyst Data & AI - Temporary will drive the design, development, and delivery of scalable data solutions while mentoring data engineers and ensuring robust data pipelines across enterprise platforms.

Responsibilities

Design & Implementation: Manage exploratory data analysis solutions, provide effort estimations, and design data models to optimize ingestion and presentation.

Pipeline Design & Development: Develop cost-effective, scalable ELT pipelines for batch and streaming data, document strategies and monitor production environments.

Environment Setup & Collaboration: Establish production and non-production environments with proper RBAC, cloud services, and Git repositories, while collaborating with product owners and cross-functional teams.

Technical Leadership & Mentorship: Mentor data engineers, document technical debt, educate on best practices, and maintain strong vendor relationships.

DevOps & Data Modeling: Lead UAT and production deployment activities and apply principles of DevOps, Star Schema, and Data Vault methodologies.

Qualifications

Professional Experience: 3-5 years leading enterprise data warehouse teams in Agile environments with cloud-based platforms like Azure and Snowflake.

Technical Skills: Expertise in SQL, Python, ETL/ELT tools (Azure Data Factory, Databricks, Snowflake, DBT, Talend), and implementation of monitoring mechanisms. Experience with GenAI is an advantage.

Education: Bachelor’s degree in Engineering, Computer Science, Mathematics, or a related field.

Soft Skills: Excellent communication, problem-solving, leadership, and collaboration skills.

Conditions Of Employment

Candidates must be eligible to work in the country of interest and provide necessary work authorization proof. Preference is given to bilingual candidates.

Diversity and Inclusion

Air Canada is committed to creating a diverse and inclusive environment where every contribution is valued.

Key skills/competency

• Data Engineering
• Azure
• Snowflake
• DevOps
• ETL/ELT
• SQL
• Python
• Data Pipelines
• Mentorship
• GenAI