AI Data & Analytics Engineer (West Bloomfield Township)

Department: Data Analytics / Finance

Division: Corporate

Job Status: Full-Time

Position Type: Permanent

Work Environment: OnsiteAbout the RoleDACUT 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.

Artificial Intelligence & Automation: 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.

Financial Analytics: 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.

Power BI & Business Intelligence: 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.

SQL & Data Engineering: 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.

Vertically Integrated Operations: 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.

Data Governance & Compliance: 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 inaccurate information. Protect confidential financial, employee, customer, and operational information. Support reporting requirements within a highly regulated industry. Ensure AI tools and data integrations follow company security, privacy, and compliance standards.

Required Qualifications: Bachelor's degree in Data Science, Computer Science, Data Analytics, Finance, Accounting, Engineering, or a related field. At least 3–5 years of experience in data analytics, business intelligence, data engineering, financial analytics, or a related position. Advanced SQL skills, including complex joins, CTEs, data transformations, query optimization, and database troubleshooting. Advanced experience developing Power BI dashboards, semantic models, Power Query transformations, and DAX calculations. Demonstrated experience applying AI, machine learning, or predictive analytics to real business problems. Strong understanding of financial statements, budgeting, forecasting, profitability, and operational finance. Experience integrating and reconciling data from multiple business systems. Ability to translate complex technical findings into clear recommendations for executives and operational leaders. Strong analytical, organizational, and problem-solving skills. Ability to work onsite at the West Bloomfield corporate office.

Preferred Qualifications: Experience supporting a vertically integrated or multi-entity organization. Experience within cannabis, manufacturing, retail, distribution, consumer packaged goods, or another highly regulated industry. Experience with Python, Microsoft Fabric, Azure, Databricks, APIs, or cloud-based data platforms. Experience building machine-learning models, AI agents, or large language model integrations. Knowledge of ERP, POS, inventory-management, payroll, and accounting systems. Experience analyzing product costing, inventory valuation, supply-chain performance, and multi-location profitability. Familiarity with cannabis platforms such as METRC, Dutchie, Alpine IQ, or similar systems. Experience developing enterprise data governance and KPI standardization.

What Success Looks Like: Leadership has timely access to accurate financial and operational insights. Manual reporting processes are replaced with reliable automated workflows. Financial forecasts become more accurate and actionable. Data from retail, cultivation, processing, inventory, and corporate systems is connected. Power BI dashboards provide a consistent view of performance across the organization. AI solutions produce measurable improvements in efficiency, profitability, and decision-making.