Data Architect - Senior (Remote) JP937

Project Name: One Data Alberta Program and Crosswalk

Scope: The Data Centre of Excellence (DCoE) requires a Senior Data Architect to support the delivery of key roadmap items for the OneData Alberta and Crosswalk initiatives.

The Government of Alberta's approach to OneData Alberta and Crosswalk initiatives is enabled through a cloud-based and on-premise Data Fabric and/ Data Mesh framework for organizing, managing, and delivering enterprise data assets. The DCoE is responsible for delivering high-value data assets and services—such as analytical models, dashboards, and visualizations—to support critical analytical, policy, and legislative functions. This role is essential to ensuring these data assets are architected, governed, and delivered in a scalable, secure, and sustainable manner.

This position provides senior-level architectural leadership and strategic direction across the OneData Alberta and Crosswalk initiatives. It includes leading foundational activities for Data Access such as schema analysis, data profiling, and the development of enterprise data architecture, enterprise data models, data quality frameworks, and metadata standards. The role also guides the design and implementation of data linkages and crosswalk frameworks, enabling integrated and interoperable data across a federated data ecosystem, and supporting the development of strategic data assets for OneData Alberta.

As a Data Architect, this role contributes deep expertise in modern data platforms, architectures, and data product development practices. It supports the evolution of a Data Centre of Excellence that delivers reusable, high-quality data products and services, enabling improved data access, advanced analytics, and data-informed decision‑making across the organization.

The role works closely with leadership, architects, delivery teams, and external partners to enable a federated data ecosystem. It requires strong stakeholder engagement, including facilitating discussions, mediating complex data relationships, and building consensus among diverse technical and business groups.

This position plays a key role in advancing the cultural shift toward treating data as a strategic enterprise asset, fostering innovation, and ensuring alignment between business priorities and data technology solutions.

Duties

General Responsibilities

Architecture & Strategy Leadership

• Lead the design and delivery of enterprise and solution architecture for data platforms, AI‑enabled data products, and data integration solutions across platforms such as Snowflake, Microsoft Azure, and Cloudera
• Provide architectural guidance in cloud environments, including solution design for AI‑enabled data products, agentic frameworks, secure data sharing frameworks, and data linkage capabilities
• Define and govern enterprise data models, architecture standards, and best practices
• Translate business strategies and priorities into scalable, secure, and high‑performing data architecture solutions
• Provide thought leadership in Data Management, Analytics, and AI‑driven architecture

Data Platform & Product Enablement

• Support the design, development, and delivery of data products within Data Fabric and/or Data Mesh frameworks across Snowflake, Microsoft Azure, and Cloudera environments
• Guide the implementation of data linkages, crosswalk frameworks, integration patterns, and secure data sharing frameworks to enable consistent, governed, and reliable data exchange
• Establish frameworks for data quality, metadata management, and AI‑enabled data assets
• Contribute to the design of semantic layers and data models that support reusable and interoperable data products
• Develop and validate proof‑of‑concept solutions, including data integration, orchestration, and AI‑enabled and agentic use cases

Stakeholder Engagement & Advisory

• Lead workshops, discovery sessions, and stakeholder engagements to define and validate requirements and business value
• Provide architectural consultation and recommendations to leadership, project teams, and stakeholders
• Prepare and deliver presentations to steering committees and senior stakeholders
• Facilitate alignment and consensus on complex data, AI, and technology solutions across diverse stakeholder groups

Governance, Standards & Innovation

• Define and promote best practices in data governance, data sharing, secure data exchange, data integration, and data quality
• Support data modernization initiatives, including cloud adoption, platform transformation, and AI enablement across Snowflake, Microsoft Azure, and Cloudera
• Evaluate and recommend emerging technologies, including AI and agentic frameworks, to optimize data product delivery, interoperability, and cost efficiency
• Ensure alignment with enterprise priorities, including security, privacy, information management, data classification, and secure data sharing standards

Delivery Support & Collaboration

• Collaborate with data architects, engineers, scientists, and product teams to ensure consistent architecture and design across initiatives
• Review solution designs, data models, and pipelines across cloud and hybrid platforms, providing guidance on optimization, scalability, and performance
• Support the development of sustainable and scalable processes for data product delivery
• Manage tasks, track action items, and elevate risks or issues as required
• Coordinate inputs, approvals, and sign‑offs across stakeholders and departments

Leadership & Organizational Enablement

• Coach, mentor, and support team members in developing innovative data and AI‑driven solutions
• Promote a client‑centric, service‑oriented delivery approach
• Foster a culture of innovation, continuous improvement, and data as a strategic asset
• Build and maintain strong relationships with internal and external stakeholders

Deliverables

• Architecture designs, models, and recommendations aligned with project and enterprise needs
• Data product, AI solution, and platform design artifacts across Snowflake, Microsoft Azure, and Cloudera
• Proof‑of‑concept implementations, including AI‑enabled and agentic use cases, and technical assessments
• Documentation supporting data linkages, semantic layers, integration patterns, and secure data sharing frameworks
• Weekly and monthly status reports
• Additional deliverables as defined by project and client teams