Data Analytics AI Engineer

Data Engineering & Analytics Platform

• Design, build, and maintain reliable, scalable data pipelines using Boomi and Azure Data Factory to integrate data from ERP, EHS, operational, and corporate systems.
• Develop and manage curated data models in Azure SQL and a future Microsoft Fabric lakehouse or warehouse architecture to support analytics, AI, and reporting.
• Ensure data quality, consistency, and performance across pipelines, models, and downstream consumers.
• Contribute to data architecture standards, patterns, and best practices as the platform evolves toward Microsoft Fabric.

Analytics & Reporting

• Develop and maintain Power BI semantic models, dashboards, and reports that deliver actionable insights to executives and business teams.
• Promote self-service analytics through well-designed datasets, documentation, and governance.

AI, Machine Learning & Agentic Workflows

• Identify, prototype, and deliver AI and machine learning solutions that improve decision-making, forecasting, anomaly detection, classification, and automation.
• Design and implement agentic workflows that combine data, analytics, and AI models to automate multi-step processes, decision support, and operational actions.
• Leverage Azure-based AI services and emerging Fabric capabilities (notebooks, ML, real-time intelligence) to put AI solutions into production.
• Act as an internal advocate and advisor on responsible AI adoption, helping teams understand practical and strategic AI opportunities.

Collaboration & Delivery

• Work with IT, security, and DevOps teams so solutions meet enterprise standards for security, compliance, and reliability.
• Partner with cross-functional teams as a resource on key initiatives.
• Prioritize, scope, and manage data and AI initiatives with clear success metrics and business outcomes.

Continuous Improvement & Innovation

• Explore, evaluate, and pilot new data, analytics, and AI technologies with a bias toward business value.
• Contribute to a culture of experimentation, continuous improvement, and data-driven decision-making.