Data Architect, IT Airline Operations

WestJet Group•Toronto, ON

2d•Onsite

About The Position

The Data Architect has end-to-end responsibility for ensuring the completeness and integrity of data architecture within Airline Operations. Operating within the domain-aligned data product model, the role is a shared, cross-pod resource that designs the conceptual, logical, and physical data architectures enabling each domain (such as Flight & Maintenance and Guest 360) to deliver source-aligned data products that serve operational, analytical, and AI / ML needs from a common foundation. This is achieved by adequately addressing the pertinent concerns of stakeholders and the integrity of the architecture, in terms of appropriate selection and structuring of data models, storage, and movement, and their adherence to corporate architectural and governance standards. The Data Architect satisfactorily reconciles the conflicting concerns of operational and analytical consumers and develops the optimal architecture within the constraints of practicality, cost, enterprise reuse, and fitness-for-purpose. The role is responsible for developing, maintaining, and ensuring the integrity of end-to-end data solutions to address specific data product, project, programme, or domain requirements and to align with enterprise data strategy, reference architectures, and engineering standards, including the common patterns and governance defined through the Data Centre of Excellence.

Requirements

Postgraduate qualification in Computer Science, Engineering, Information Systems, Data / Information Management, or a related field and 5+ years of relevant experience preferred, or an equivalent combination of training and experience.
Demonstrated leadership skills, providing mentorship and technical guidance to other team members.
Expert problem-solving skills and advanced interpersonal and communication skills, including influencing others.
Strong expertise in data modelling (conceptual, logical, and physical) and in canonical and domain modelling.
Strong expertise in modern data platforms — cloud data warehousing (Snowflake) and operational data stores.
Strong expertise in data integration and movement, including APIs and web services.
Strong understanding of data governance, data quality, and metadata management.
Strong understanding of data privacy and security controls and applicable regulatory requirements, including PCI, PIPEDA, GDPR, and CCPA.
Strong understanding of AI / ML data enablement — feature readiness, metadata for ML, and operational and analytical serving.
Intermediate understanding of architecture frameworks and modelling languages, including TOGAF, ArchiMate, and the C4 model.
Intermediate knowledge of programme, project, and agile methodologies and their applicability to the successful delivery of data change.

Nice To Haves

Current data architecture, data platform, and / or cloud certification(s) preferred (e.g. Snowflake, TOGAF).
Knowledge of airline operations data domains and relevant interchange and industry standards — including familiarity with IATA AIDX and PADIS — an asset.

Responsibilities

Leading the design of conceptual, logical, physical, and semantic data architectures and models for complex data products, showing multiple views to communicate effectively and ensuring consistency with agreed requirements and a source-aligned, reusable design.
Defining and maintaining the canonical and domain data models and taxonomies for Airline Operations, distinguishing core domains, foundational layers, data products, and interchange standards.
Establishing and maintaining the policies, principles, and standards for the selection of data architecture components — storage (cloud data warehouse / Snowflake, operational data stores), modelling approaches, and serving / semantic layers — aligned to corporate standards bodies such as Architecture Boards and Data Governance forums.
Designing ingestion, integration, and transformation patterns that reduce handoffs and enable single-team, end-to-end pod delivery.
Developing end-to-end data products that serve both operational and analytical needs from the same source-aligned dataset, ensuring AI / ML readiness through appropriate metadata and feature readiness, and providing scalable, reliable, and resilient data capability to users.
Managing trade-offs and balancing functional, data quality, performance, and operability requirements within a significant data domain or value stream of the organization.
Embedding data governance, data quality, and metadata into data product design, in partnership with the Data Governance function and Centre of Excellence.
Considering requirements for data privacy, security, classification, retention, and testing across the full data lifecycle.
Ensuring that existing and planned data components are compatible with relevant architectures, strategies, policies, standards, and practices, and adhere to the federated model with central oversight.
Being accountable for data roadmaps — high-level views of data capability and platform evolution from which plans are created — including migration to appropriate cloud services, enterprise reuse opportunities, investment priorities, and AI-readiness.
Defining the planned operation and maintenance of data solutions within a production environment — including the IT support functions and infrastructure required, and changes to data services, processes, organization, and operating models as well as technology.
Coordinating and managing the target data architecture across multiple data product pods, WestJet business units, and third-party suppliers or partners (including vendor / RFP delivery capacity), maintaining a stable, viable architecture and consistency of design.
Providing guidance and risk-based governance to support data product implementation, including managing requests for change and deviations from specification.
Being accountable for the completeness (fitness-for-purpose) of the data architecture by adequately addressing the pertinent concerns of its stakeholders and reconciling the conflicting concerns of operational and analytical consumers, leading to sign-off of the data design as fit for purpose.
Understanding and interpreting requirements by probing for information, influencing people, facilitating consensus, and synthesizing and translating ideas into actionable data designs embodied in the architecture specification.
Tracking and evaluating emerging trends in data architecture, data platforms, and AI / ML enablement, maintaining strong knowledge of the technologies, techniques, and business concepts used within the domain, and sustaining strong relationships with appropriate vendors.
Collaborating with and mentoring Data Product Owners, data engineers, integration specialists, analysts and modelers, solution architects, governance analysts, and business SMEs to deliver optimal, enterprise-aligned data solutions — providing thought leadership that acts as a catalyst for change while remaining open minded to other ideas.
Presenting concepts to senior leaders as necessary, up to and including the CEO, while explaining technical data concepts in an appropriate manner for non-technical audiences.