Azure Cloud Engineer Jobs in Saskatchewan (NOW HIRING)

Out-of-scope
Permanent, Full-Time

Work Location: Regina, Head Office. This role is eligible for a hybrid work option in Regina. Remote work may be considered if you reside outside Regina but within Saskatchewan.

Pay Range: $109,052 - $145,411
Posting Close Date: September 12, 2026

General Accountability

The Data Solution Architect is a specialised technical position responsible for translating data designs into scalable, secure, and production-ready platform solutions that support enterprise data and analytics capabilities. As a Data Solution Architect, you will define how data architecture is implemented through end-to-end solution designs that align with platform infrastructure, integration patterns, and enterprise standards. Working closely with the Data Architect, Data Engineers, and IT stakeholders, you will ensure data solutions are implementable, sustainable, and aligned with the data platform strategy.

Key Accountabilities

Note: This section is not intended to be an exhaustive list of duties and responsibilities - other duties and responsibilities may be assigned.

Solution Enablement

• Designs and architects modern, scalable, and composable data platforms across multi-cloud environments (Amazon Web Services (AWS), Azure), supporting real-time analytics, artificial intelligence (AI)/machine learning (ML), and customer experience use cases.

• Assesses data ecosystems and develops strategic modernization roadmaps, guiding the transition from on premises to cloud and enabling unified data and activation.

• Implements and enforces architectural standards, governance practices, and reference architectures while designing and delivering data solutions based on established architectural patterns.

• Evaluates and recommends data storage and computes technologies (e.g., Fabric, Snowflake, Redshift, Delta Lake, Apache Iceberg) based on performance, scalability, cost, and security trade-offs.

• Designs robust, scalable extract, transform, load (ETL) and extract, load, transform (ELT)\ pipelines using both batch and streaming tools (e.g., Data Build Tool (dbt), Airflow, Kafka, Pub/Sub) and optimizes data flows for speed and reliability.

• Develops architectural guidance for AI/ML data pipelines, including the design of feature stores, real-time inference pipelines, and Machine Learning Operations (MLOps) alignment.

• Provides strategic advisory to business and technical stakeholders, aligning data architecture decisions with broader digital & data transformation and return on investment (ROI) goals.

• Creates clear, business value deliverables: reference architectures, integration strategies, migration plans, and governance models.

• Architects AI ready data foundations supporting model training, experimentation, and production deployment

• Designs feature stores and reusable feature engineering frameworks and enables real-time inference pipelines and event-driven AI use cases.

• Aligns data architecture with MLOps best practices (model versioning, monitoring, integration)

• Supports large language model (LLM) and generative AI integration through vector stores, embeddings, pipelines, and scalable model-serving infrastructure.

Planning and Strategy Support

• Partners with business, analytics, and technology teams to define and evolve data architecture, cloud data platform capabilities, and reporting frameworks, translating current and future business needs into scalable, governed, and high-performing data solutions.

• Maintains knowledge of emerging architecture, analytic techniques and trends to educate the Data Office, IT, and business teams.

• Collaborates with business and technology subject-matter experts to design representative and effective data architectures and data integration patterns.

• Contributes to data platform strategy by designing solutions that enable data readiness, ensuring underlying data is integrated, governed, and structured to support analytics, AI/ML, and enterprise reporting.

• Continuously reviews the data landscape to identify risks, technical debt, and improvement opportunities, and provides architectural direction to support modernization and improve data accessibility and analytics capabilities.

• Contributes technical expertise during Request for Proposal (RFP) processes by assisting in the development of technical RFP requirements and participating in the evaluation of RFP responses and recommendations.

Delivery and Support

• Ensures data solutions are implementedacross data platformsinalignmentwith approveddata architecturestandards and integration patterns.

• Ensures solution designs are actionable and implementable, supporting efficient build, deployment, and operationalization within the data platform.

• Identifies technology interactions and dependencies across systems, data platforms and reporting tools that impact integration, performance, scalability and compatibility.

• Conducts research and provides recommendations for solution delivery of the enterprise data platform and reporting ecosystem.

• Ensures solutions follow security policies and comply with established enterprise architecture principles.

• Partners with IT and Data Office teams on enterprise-wide data initiatives, platform enhancements, and production support to ensure reliability, performance, and operational stability of data solutions.

Leadership

• Actively contributes to and supports a culture of a high performing workforce.

• Participates in divisional succession plans, ensuring ongoing professional and career development and supports development in others.

• Supports a culture of leadership and accountability to effectively deliver on strategic and corporate strategies.

• Is actively committed to leadership development across the company, supporting team and workforce readiness through mentoring, training and developmental opportunities.

Corporate Management

• Enables the success of programs and policies that are in alignment with corporate, strategic and divisional strategies.

• Manages risk in area of authority.

• Ensures that the Health, Safety and Emergency Management Policy is applied in area of responsibility.

Education and Experience

• Four-year degree from an accredited post-secondary education institution in a relevant field of study, such as Computer Science, Information Technology, Mathematics & Applied Science, Engineering, or defined equivalency.

• Six years' experience in data engineering, and enterprise data solutions, with progressive involvement in data architecture, Azure and cloud-based data platforms, and data integration initiatives.

Knowledge, Skills and Abilities

• Knowledge of enterprise data architecture principles, including data platform design, modern data architectures (Lakehouse, Medallion, Data Vault, and Data Mesh), and scalable data ecosystems supporting analytics, AI/ML, and enterprise reporting.

• Knowledge of data modeling techniques, including gathering, inspection, cleansing, and transformation of data.

• Knowledge of solution design, database design and management, application integration, agile implementation, and cloud-based platforms.

• Knowledge of Azure cloud data platform components: Azure Data Lake, Cosmos DB, Synapse Analytics, Databricks, Azure Data Factory, Blob Storage, Azure Stream, and cloud best practices.

• Knowledge of modern data platform technologies across cloud ecosystems, including platforms such as Snowflake, Delta Lake, Apache Iceberg, Amazon Redshift, and emerging data ecosystem tools.

• Knowledge of cloud cost management and optimization strategies across storage, compute, and data pipelines.

• Knowledge of Property and Casualty industry data, products, and services.

• Skill in using data modeling and architecture tools, understanding physical implementation, design implications, and performance requirements.

• Ability to translate business and architectural requirements into implementable data solutions.

• Ability to design scalable, cost-effective, secure, and integrated data solutions that align with business strategy and enable reliable data use across the organization.

Behaviourial Competencies

Leader Level 4 - Applies (Department/Division)

• Accountability - Enables Performance Across Teams/Business Units

• Business Acumen - Formulates Departmental/Divisional Plans in Relation to Internal and External Environment

• Change Agility - Defines Areas for Change and Follows Through

• Leadership - Leads the Department/Division

At SGI, we are committed to a workplace where people feel respected, valued, and able to contribute fully. Through fair, consistent, and transparent people practices, we attract skilled talent with varied lived experiences and offer meaningful work, opportunities for growth, and a strong sense of belonging. Our commitment to reconciliation includes inclusive hiring practices that create meaningful opportunities for Indigenous peoples and support a workforce reflective of the communities we serve. Join us in building a culture where contributions are valued and shared success is shaped by our people.

If yourequirean accommodationduring the recruitment process, we invite you tosubmityour accommodation request toemployeeleaves@sgi.sk.caand we will work through your request with you. All information received will be kept confidential.

Posting Close Date: