Data Architect

Transat AT•Montreal, QC

13d•Hybrid

About The Position

In collaboration with the Director, Data & Analytics Solutions, the incumbent defines, evolves, and maintains the target data architecture and business intelligence ecosystem. The person in this role designs scalable, modern, and AI-ready data solutions while ensuring data consistency, governance, and business value across the organization.

Requirements

University degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
Minimum of 8 years of experience in Data Architecture and more than 12 years of experience in Information Technology.
Proven expertise in Data Warehousing, Data Vault 2.0, Lakehouse architectures, Data Mesh, enterprise data governance, quality management, security, and cataloging.
Strong leadership, communication, stakeholder management, strategic thinking, and influencing skills.
Solid understanding of Artificial Intelligence, Machine Learning, Large Language Models (LLMs), Generative AI, and their practical application within enterprise data ecosystems.
Experience with cloud data platforms, streaming technologies (Snowpipe Streaming, Kafka, Azure Event Hubs), enterprise data catalogs (Purview, Collibra, Alation), semantic layers, and cloud cost optimization, particularly Snowflake credit management.
Advanced proficiency with Snowflake, Microsoft Fabric, Azure Data Platform, BigQuery, Power BI, SQL, Python, DBT, and a demonstrated ability to leverage collaborative digital tools and AI technologies (e.g., Copilot).
Ability to quickly learn and adapt to new technologies.
Oral and written fluency in French and English.
A good knowledge of French is required for positions in Quebec. The incumbent will be required to communicate and collaborate frequently in English, both orally and in writing, with colleagues, customers, and other stakeholders in Quebec, the rest of Canada, and internationally.

Nice To Haves

SnowPro Advanced Architect certification or equivalent is considered an asset.
Experience working with loyalty programs.
Experience in the aviation, travel, or airline industry.

Responsibilities

Define, document, and maintain target data architectures, including Data Warehouse, Data Lake, Lakehouse, and BI solutions across modern cloud platforms such as Snowflake, Azure, Microsoft Fabric, Power BI, dbt, and BigQuery.
Design and evolve enterprise data models, including dimensional, Data Vault 2.0, and BI semantic layer architectures.
Ensure data integration and consistency across multiple enterprise systems, including ERP, CRM, CRS, DCS, and other airline-related platforms.
Establish standards and best practices for data modeling, integration, transformation, quality, governance, cataloging, lineage, and security.
Design AI-ready architectures that support advanced analytics, machine learning, predictive models, personalization, optimization, and generative AI use cases.
Promote DataOps, DevOps, CI/CD, and MLOps practices, including automated testing, deployment, monitoring, and continuous improvement of data pipelines.
Collaborate with enterprise architects, solution architects, data engineers, BI teams, and business stakeholders to align data strategy with organizational objectives.
Monitor industry trends, evaluate emerging technologies, and recommend strategic data and AI initiatives that enhance business value and operational efficiency.