About the Role

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. Key Responsibilities

Semantic Modelling & Metric Ownership

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. Requirements, Definitions & Stakeholder Partnership

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. Quality Assurance

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. Data Governance & Documentation

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. AI & Automation Enablement

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. Front-End Support

Ensure the semantic layer makes report-building highly efficient and self-serviceable for business users, providing overflow Power BI report-development support as needed. Qualifications & Experience





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. Working knowledge of

dbt (Data Build Tool)

and

Medallion Architecture

(Bronze, Silver, Gold structures) is a major asset. Demonstrated experience acting as a data QA/validation resource, plus experience using

Azure DevOps (ADO)

or Jira for sprint planning and requirement gathering. Familiarity with ERP ( Microsoft Dynamics 365 F&O; ) and CRM ( Salesforce / D365 CRM ) data structures is a strong asset. 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. Other

Office based role Why This Role Matters

The Data Solutions Specialist guarantees that SMART measures the right things, defined correctly, on data that is trustworthy and ready to use — the foundation that makes reporting reliable, self-service BI secure, and AI dependable. If you take pride in getting the details right and want your work to scale across the enterprise, this is where you make a tangible impact.

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📌 Data Solutions Specialist (Winnipeg)
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