Role Description The Data & Reporting Analyst will support business decision-making by developing reliable reports, dashboards, analytical models, and data solutions. The role will work across finance, operations, sales, and other business functions to translate requirements into practical insights and process improvements. The ideal candidate will combine strong analytical thinking with technical capability in Power BI and Python. This opportunity is well suited to someone with 2–5 years of experience who is excited to grow alongside a rapidly evolving Data Management & Enablement team. - Develop and maintain Power BI dashboards, reports, KPIs, semantic models, and analytical solutions that support business decision-making. - Use Python for data analysis, automation, data processing, validation, and integration-related activities. - Extract, clean, transform, validate, and analyze data from multiple business systems. - Gather and document business requirements and translate them into clear, scalable reporting and data solutions. - Analyze data from ERP, CRM, financial, operational, and other enterprise systems to identify trends, risks, and opportunities. - Improve data quality, reporting consistency, documentation, and governance across business functions. - Partner with business and technical teams to support data projects, process improvements, and new analytics initiatives. Qualifications - University bachelor’s degree in finance, Accounting, Economics, Business Intelligence, Data Analytics, Computer Science, or a related field. - 2-5 years of progressive experience in business intelligence, data analytics, financial analysis, or a related role, preferably in industrial supplies, MRO distribution, or post-merger environments. - Experience with Power BI is required. - Experience with Python for data analysis, automation, or data processing is required. - Experience with analytics and reporting platforms such as Microsoft Dynamics, Tableau, Smartsheet, or similar tools is considered an asset. - Experience using Visual Studio Code, Postman, GitHub, APIs, and version-control practices is considered an asset. - Knowledge of machine learning, generative AI, prompt engineering, or LangChain is considered an asset. - Experience with Azure, Snowflake, or other enterprise data management platforms is considered an asset. Requirements - In accordance with the provincial wage transparency requirements, the expected base compensation for this position is $65,000-$75,000 depending on relevant experience, technical competencies, certifications, etc. Benefits - Medical, Dental, Vision, STD/LTD/AD&D, Life Insurance, RRSP Matching, Pro-rated Vacation Entitlement, Paid Statutory Holidays, Employee Assistance, etc. - Competitive compensation that recognizes your worth. - A flexible health, drug, and dental plan tailored to your well-being. - An employer-matching retirement savings plan for your financial security. - Additional life and disability insurance options for peace of mind. - Confidential access to an Employee Family Assistance Program (EAP) that supports your holistic welfare. - An enriched vacation entitlement schedule for a balanced life. - Participate in our physical fitness reimbursement program, championing your vitality.

• Help clients maximize value from their marketing data. • Own client delivery end-to-end for assigned accounts — from data modeling through final reporting. • Design and maintain dashboards across BI platforms, ensure data quality, and deliver clear, actionable reporting. • Manage data transformations in dbt and work with complex, multi-source data architectures. • Utilize AI tools to accelerate workflows. • Proactively identify opportunities, trends, or risks in marketing data and communicate findings clearly.

• Help clients maximize value from their marketing data. • Own client delivery end-to-end for your assigned accounts — from data modeling through final reporting. • Design and maintain dashboards across BI platforms, ensure data quality, and deliver clear, actionable reporting. • Manage data transformations in dbt and work with complex, multi-source data architectures. • Leverage AI tools (e.g. Codex, Claude) to accelerate workflows. • Write, optimize, and troubleshoot SQL queries for reporting, analysis, and investigations. • Conduct QA/UAT to ensure data accuracy, consistency, and trustworthiness. • Use Git for version control and collaboration. • Proactively identify opportunities, trends, or risks in marketing data and communicate findings clearly.

• Lead the Enterprise Data Governance function by defining and implementing governance frameworks, policies, standards, and operating models across the organization • Establish and maintain data ownership and stewardship structures to ensure accountability for critical data assets across business functions • Form, facilitate, and support Enterprise Data Governance Councils and working groups to align priorities, standards, issue resolution, and governance adoption • Partner with business and technology stakeholders to embed governance practices into operational and strategic initiatives • Promote enterprise-wide adoption of governance principles and foster a culture of accountability and data-driven decision-making • Develop and implement enterprise data quality management practices, including monitoring, measurement, remediation, and continuous improvement processes • Establish governance processes for data issue identification, prioritization, escalation, and remediation • Define and track critical data quality metrics and governance KPIs to measure program effectiveness and business value • Partner with business and technology teams to address root causes of data quality issues and improve data reliability across critical domains • Lead the implementation and governance of metadata management capabilities, including data catalog, business glossary, and data lineage • Manage enterprise business glossary and critical data elements to ensure consistent definitions and common business understanding across the organization • Drive lineage and traceability across critical business processes and reporting environments to improve transparency, trust, and audit readiness • Partner with data owners and stewards to improve metadata coverage, quality, and adoption across the enterprise • Establish standards and processes for metadata management and catalog governance • Partner with analytics and reporting teams to enable governed self-service analytics, standardized reporting, and trusted decision-making • Support the development and adoption of common KPIs, business definitions, and reporting standards to reduce reporting inconsistencies • Collaborate with business intelligence, analytics, and technology teams to improve accessibility and usability of trusted enterprise data assets • Promote data literacy, stewardship engagement, and governance awareness through training, communications, and change management activities • Prepare and deliver governance program updates, scorecards, and executive presentations summarizing progress, risks, opportunities, and measurable outcomes • Monitor governance program maturity and identify opportunities to improve adoption, effectiveness, and business value realization • Ensure governance initiatives remain aligned with enterprise priorities and strategic objectives.