Data Solutions Specialist

SMART Technologies • Calgary, AB

8d • Onsite

About The Position

As a Data Solutions Specialist at SMART Technologies, you are the connective tissue between the business, our data engineers, and the reporting that reaches decision-makers. Working within our Data Lakehouse, you will turn our governed data into a well-modelled, thoroughly documented semantic layer, forming the single source of truth that every report, self-serve query, and AI agent depends on. This is a technical role spanning the full analytics lifecycle, including capturing business use cases and building stakeholder relationships, modelling and stewarding the semantic layer, and act as a dedicated QA and validation partner across the analytics lifecycle. It requires strong skills in Power BI, DAX, Data Modeling, and Data Governance. Critically, you will structure the foundation that makes SMART's AI and automation initiatives genuinely dependable; the context that lets SMART’s AI agents return consistent, correct answers. If you are passionate about precision and thrive at the intersection of business and technology, this is your opportunity to shape the future of data at SMART.

Requirements

• Bachelor’s degree in Computer Science, Data Analytics, Information Systems, or a related quantitative field.
• 5+ years preferred in BI Development, Analytics Engineering, or a closely related data role (ideally in technology or manufacturing).
• A minimum of 3+ years of demonstrated depth in Power BI semantic modelling, DAX programming, and data governance frameworks.
• Working knowledge of SQL — able to read, write, and reason about database queries well enough to validate backend results on cloud data warehouses like Snowflake.
• Solid grasp of dimensional modeling (Star Schema, Kimble) and how data should be shaped for enterprise reporting.
• Demonstrated experience acting as a data QA/validation resource, plus experience using Azure DevOps (ADO) or Jira for sprint planning and requirement gathering.
• Comfort using AI-assisted tooling with the discernment to validate outputs rather than trust them blindly.
• Excellent communication and facilitation skills; able to translate between business and technical audiences, with a collaborative, continuous-learning mindset.
• Collaborative, agile mindset and a commitment to continuous learning.

Nice To Haves

• Working knowledge of dbt (Data Build Tool) and Medallion Architecture (Bronze, Silver, Gold structures) is a major asset.
• Familiarity with ERP (Microsoft Dynamics 365 F&O) and CRM (Salesforce / D365 CRM) data structures is a strong asset.

Responsibilities

• Design, build, and maintain Power BI semantic models on top of analytics-ready data assets — managing relationships, complex DAX measures, calculation logic, and Row-Level Security (RLS).
• Steward the single source of truth for metric and KPI definitions, ensuring a given measure resolves the same way across every report, self-serve query, and AI agent.
• Optimize semantic models for accuracy, performance, and scalability, and partner closely with Data Engineers to ensure data assets cleanly support the semantic layer.
• Engage cross-functional stakeholders across Sales, Marketing, Operations, Product, and Finance to gather requirements and define trusted KPIs.
• Translate business questions into modelled, testable data solutions, ensuring consistency in business rules and definitions across departments.
• Create and manage user stories on the Azure DevOps (ADO) board with clear requirements, acceptance criteria, and alignment to business priorities.
• Serve as the QA partner the full data pipeline, ensuring models are validated before they are trusted or promoted.
• Validate ingestion is complete, transformations are accurate, aggregates tie out to source and business definitions, and measure/model changes pass regression checks.
• Log, track, and partner with data engineers to resolve issues found in QA.
• Champion strong enterprise Data Governance standards — maintaining version control, access standards, and data integrity across all corporate reporting.
• Create and maintain a living enterprise data dictionary, measure catalogue, and semantic-layer documentation, with definitions precise enough to be unambiguous to both people and AI models.
• Structure and maintain the semantic context (metric definitions, documentation, lineage) that grounds SMART's AI agents so they return consistent, trustworthy answers.
• Identify and implement opportunities to automate recurring documentation, data analysis, QA, and semantic-model maintenance using AI-assisted tooling.
• Ensure the semantic layer makes report-building highly efficient and self-serviceable for business users, providing overflow Power BI report-development support as needed.

Benefits

• award-winning company
• collaborates with bright minds around the world
• Best in Class culture
• meaningful work that fuels connections across the globe

What This Job Offers

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