Senior Data Architect

Job Title: Senior Data Architect Location: Remote, Canada Seniority on the skill/s required on this requirement: Senior Estimated Duration: 1 year with possible extension to another 1 year Work authorization: any (candidate must be authorized to work in CA) Job Description We are seeking a Senior Data Architect to provide architectural leadership and strategic direction for a high-profile, enterprise-wide data transformation initiative. Operating within a mature Data Centre of Excellence, this role is critical to designing, governing, and delivering scalable, secure, and sustainable data assets across combined cloud and on-premise environments. The ideal consultant will bring deep expertise in modern data platforms, data product development practices, and federated data ecosystems to help advance a cultural shift toward treating data as a strategic enterprise asset. 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 escalate 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 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 Requirements The proposed resource must meet or exceed one of the following: University graduation in business, management or a related discipline and 6-yr Data Architect (DA) experience; OR 2-yr diploma in business, management or a related discipline and 8-yr DA experience; OR 1-yr certificate in business, management or a related discipline and 9-yr DA experience; OR 10-yr DA experience. Experience dealing with clients and explaining complex data principles in a thoughtful manner. Experience in defining technical architecture, data integration, supporting software development, software configuration and deployment processes. Experience designing, planning, implementing and supporting infrastructure and application solutions in an architecture capacity for an environment equivalent in size and complexity to the Government of Alberta. Experience in multiple architecture domains e.g. business, application, technology, data/information, security, and privacy. Experience modelling complex business processes and translating them into understandable IT constructs. Demonstrated ability to lead initiatives, facilitate workshops, and communicate effectively with senior management and cross-functional stakeholders; includes planning, estimation, presenting data and AI solutions and standards, and risk assessments. Direct, hands-on experience in business requirements analysis, architecture and design, and end-to-end delivery of cloud-based data and analytics solutions using platforms such as Snowflake, Microsoft Azure, and Cloudera. Includes data management, engineering, visualization, advanced analytics/data science, AI-enabled data products, and exposure to agentic frameworks and AI-driven orchestration patterns. Direct, hands-on experience leading business requirements analysis, solution architecture, design, and deployment of enterprise data and AI platforms. Includes data migration from legacy systems to modern platforms, covering data acquisition, transformation, data modeling, quality, metadata management, lineage/provenance, data integration, data linkages, crosswalk frameworks, master/reference data alignment, and migration from legacy systems to modern platforms. Experience designing and delivering scalable, reusable data products (e.g., curated datasets, APIs, semantic layers) that are consumable across the organization. Includes implementation of secure data sharing frameworks, data access patterns, and governance to enable analytics, reporting, and AI/ML use cases. Experience designing architectures that support machine learning, data science, and advanced analytics, including feature engineering, model training pipelines, MLOps, model monitoring, and lifecycle management. Includes exposure to agentic frameworks, autonomous decisioning systems, and orchestration of AI-driven workflows. Experience designing solution architectures for AI-enabled data products, including agentic frameworks, AI orchestration, and intelligent automation. Includes integration of AI services with data platforms, governance of AI workflows, and alignment with enterprise architecture and security standards. Experience developing and delivering training materials and enabling teams on data, analytics, and AI best practices, governance, and platform adoption. Experience with Big Data and cloud-based platforms (e.g., Snowflake, Microsoft Azure, Cloudera Data Platform) and modern architectural paradigms such as Data Fabric and Data Mesh. Familiarity with AI/ML platforms, semantic layer design, and distributed data architectures in cloud ecosystems Experience with enterprise architecture frameworks (e.g. The Open Group Architecture Framework (TOGAF), Gartner or Zachman). Experience working in or for the public sector. Hands-on experience implementing data security and privacy controls, including policies, de-identification/anonymization, and data audits. Hands-on experience implementing enterprise data strategy, governance, and secure data sharing frameworks. Includes data security and privacy controls, data classification, de-identification/anonymization, and data audits. Familiarity with Responsible AI principles (e.g., fairness, bias detection, explainability) and risk assessments with mitigation recommendations. Work experience with Responsible AI principles (e.g., fairness, bias detection, explainability) and conducting risk assessments with mitigation recommendations for senior leadership. Mindtris, a minority women-owned enterprise, is at the forefront of digital transformation, technology excellence, and business growth solutions. Specializing in talent mobilization and innovation, we are dedicated to enhancing customer experiences across diverse sectors such as Information Technology, Telecommunications, Healthcare, Engineering, and the Public sector. With a focus on deploying top-tier talent and fostering innovation, we empower businesses to thrive and excel in a rapidly evolving digital landscape, helping them reach new heights of success. Mindtris is committed to fostering workforce diversity and is proud to be an equal opportunity employer.

The Senior Data Architect will lead the design and delivery of enterprise architecture for data platforms and AI-enabled data products. This role involves providing architectural guidance, defining enterprise data models, and supporting data product development within cloud and on-premise environments.

Candidates must have extensive experience in data architecture, with a minimum of 10 years in the field. They should possess strong skills in cloud-based data solutions, data governance, and the ability to communicate complex data principles effectively.

Identified from the job description. Confirm important requirements above.

• Data Architecture
• Cloud Platforms
• Data Integration
• AI Products
• Data Governance
• Data Quality
• Data Modeling
• Stakeholder Engagement
• Data Security
• Data Management
• Big Data
• Data Fabric
• Data Mesh
• Machine Learning
• Advanced Analytics
• Semantic Layer Design

• Technology
• Data & Analytics
• Consulting
• Engineering
• Government & Public Sector

Minimum education

Bachelor’s degree

Minimum experience

10+ years

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level

Application method

Direct apply is available