AI Data & Analytics Engineer

DACUT Cannabis is seeking an experienced AI Data & Analytics Engineer to build intelligent reporting, automation, and forecasting solutions across our vertically integrated cannabis organization.

This position will combine artificial intelligence, financial analytics, SQL, Power BI, and data engineering to improve decision-making across retail, cultivation, processing, distribution, and corporate operations. The AI Data & Analytics Engineer will transform complex financial and operational data into scalable dashboards, predictive models, automated workflows, and actionable business insights.

The ideal candidate has strong technical experience with AI-powered analytics, financial modeling, SQL development, and Power BI. Experience supporting a vertically integrated, multi-location organization is highly preferred.

• Develop and implement AI-powered tools that improve forecasting, reporting, operational efficiency, and financial decision-making.
• Build machine-learning models for revenue forecasting, demand planning, inventory optimization, labor analysis, and expense management.
• Identify opportunities to automate recurring financial, operational, and executive reporting.
• Develop AI-assisted workflows using large language models, APIs, and automation platforms.
• Create systems that identify trends, anomalies, financial risks, and operational inefficiencies.
• Evaluate emerging AI technologies and recommend practical applications across the organization.
• Establish safeguards and validation processes to ensure AI-generated insights are accurate, secure, and reliable.
• Analyze revenue, gross margin, operating expenses, labor costs, inventory value, profitability, and cash-flow trends.
• Build financial models, forecasts, budgets, and scenario analyses for executive leadership.
• Develop location-level, department-level, product-level, and brand-level profitability reporting.
• Analyze performance across retail, cultivation, processing, distribution, and corporate operations.
• Partner with Finance and Accounting to validate financial data and maintain consistent reporting standards.
• Create automated reporting for actual performance compared with budgets, forecasts, and prior periods.
• Support strategic planning by identifying cost-saving opportunities, revenue trends, and performance risks.
• Design, develop, and maintain executive-level Power BI dashboards and reporting tools.
• Build scalable data models using Power Query, DAX, calculated measures, and relationships.
• Create dashboards for financial performance, retail sales, inventory, cultivation yields, production output, labor, and operational KPIs.
• Implement row-level security, scheduled refreshes, and data-quality controls.
• Improve dashboard usability by presenting complex information in a clear and actionable format.
• Establish consistent definitions for KPIs across departments and business entities.
• Write, optimize, and maintain complex SQL queries, stored procedures, views, and data transformations.
• Build and manage ETL/ELT pipelines that consolidate information from multiple systems.
• Integrate data from POS, ERP, accounting, payroll, inventory, compliance, CRM, and operational platforms.
• Create centralized datasets that support reporting, forecasting, and AI applications.
• Monitor data pipelines, troubleshoot failures, and resolve inconsistencies between source systems.
• Develop processes for data cleansing, validation, reconciliation, and documentation.
• Support the development of a reliable data warehouse or centralized reporting environment.

• Connect data across retail, cultivation, processing, distribution, inventory, finance, and corporate functions.
• Develop reporting that tracks products and costs throughout the entire operational lifecycle.
• Analyze cultivation yields, production costs, inventory movement, retail sell-through, product margins, and overall profitability.
• Identify gaps between departments that affect data accuracy, inventory control, or financial performance.
• Partner with leaders across each division to understand operational challenges and develop data-driven solutions.
• Support standardized reporting across multiple locations, departments, brands, and legal entities.

• Maintain accurate, consistent, and secure financial and operational data.
• Develop documentation for data sources, models, calculations, dashboards, and automated processes.
• Establish validation controls to identify missing, duplicated, or…