Data Solutions Analyst, Business Enablement

Steel Reef Infrastructure Corporation • Calgary, AB

12h • Hybrid

About The Position

Steel Reef is seeking a Data Solutions Analyst to join their Calgary team. This role is responsible for designing, building, and supporting scalable, secure, and business-aligned data solutions to improve reporting, analytics, automation, and data-driven decision-making. It is a hands-on, delivery-focused position that involves data development, software development, and integration development. The analyst will work within Microsoft Fabric to build data pipelines, develop Python notebook solutions, and integrate data across enterprise systems, ensuring reliability, maintainability, and alignment with business needs. Collaboration with business stakeholders, the Business Enablement team, and technical partners is key to translating requirements into practical data and integration solutions. The role also supports AI and advanced analytics capabilities, aiming to leverage data for operational efficiency, innovation, and growth, while enhancing data quality and creating reusable, scalable data assets.

Requirements

• Post-secondary education in computer science, information systems, engineering, data analytics, or a related discipline, with experience in data development, analytics engineering, or a similar technical role.
• Hands-on experience with Microsoft Fabric (or similar platforms), including development using Python notebooks, SQL, and data transformation techniques.
• Experience with PySpark / Spark, Power BI (semantic models/reporting), and Git-based development practices.
• Experience integrating enterprise systems (APIs, file-based ingestion) into analytics platforms.
• Experience building and supporting data pipelines, integrations, and curated datasets, with working knowledge of medallion architecture, data modeling, and analytics structures.
• Understanding of data quality, validation, governance, security, and best practices across cloud data platforms, including exposure to CI/CD, APIs, and DevOps workflows.
• Strong analytical, problem-solving, and communication skills, with the ability to collaborate with stakeholders and translate business requirements into practical data solutions.

Responsibilities

• Design, build, and maintain scalable data pipelines, transformations, and reusable data assets to support analytics and reporting needs.
• Develop data solutions in Microsoft Fabric using Python notebooks for ingestion, transformation, and data processing.
• Implement and support medallion architecture (bronze, silver, gold layers) to improve data quality, structure, and usability.
• Translate business and reporting requirements into practical data designs and technical solutions.
• Design and support scalable data models, transformation processes, and integration patterns.
• Identify effective approaches for ingesting, storing, transforming, and serving data for analytics and reporting.
• Develop and deliver solution components (e.g. services, integrations, automation scripts, applications, or platform extensions) required to implement design solutions.
• Contribute quality code including unit tests and technical documentation to support maintainability and long-term support.
• Partner with business stakeholders to understand data needs, reporting objectives, and process challenges.
• Work closely with the Business Enablement team to deliver data solutions that support decision making and operational efficiency.
• Support solution development and adoption through participation in discussions, requirements clarification, and documentation/knowledge transfer.
• Identify opportunities to simplify data processes, reduce manual effort, and improve reusability of data assets.
• Contribute to standards, templates, and development practices for notebook development, data pipelines, and analytics engineering.
• Promote good development practices including version control, peer review, testing, and documentation.
• Stay current with evolving Microsoft Fabric capabilities, AI roadmaps, and data engineering best practices.

Benefits

• Competitive compensation and bonus programs
• Competitive benefit package, including a Flex Spending Account and Savings Plan matching
• Monthly phone allowance
• 8 hours of annual paid Volunteer time to support the communities in which we operate
• Team building activities
• Various recognition reward programs including long-term service awards and value-based awards

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level