Data, Analytics & AI Engineer
On-siteBirmingham, Alabama, United States
Job Summary
Design, build, and maintain scalable data pipelines using Azure Data Factory and Boomi to integrate ERP, EHS, and operational systems. Develop curated data models in Azure SQL while migrating architectures to Microsoft Fabric Lakehouse and Warehouse environments. Build interactive dashboards and semantic models in Power BI to translate business questions into actionable KPIs and enable self-service reporting. Design, prototype, and deploy AI and Machine Learning solutions, including agentic workflows that automate multi-step processes using Azure AI services and notebooks. Partner with IT, Security, DevOps, and business leaders to deliver secure, scalable solutions and manage projects with measurable outcomes. Evaluate emerging technologies and recommend improvements that create measurable business value across the organization.
Required Qualifications
- Bachelor's degree (or higher) in Computer Science, Data Science, Engineering, Statistics, Applied Mathematics, or a related field
- Strong experience building enterprise data pipelines using Azure Data Factory, Boomi, or similar integration tools
- Excellent SQL skills with experience designing relational data models
- Experience with Azure SQL Database or similar database technologies
- Hands-on experience building Power BI semantic models, dashboards, and reports
- Programming experience with Python, including notebooks and data engineering workflows
- Practical experience applying AI and Machine Learning to solve real business challenges
- Strong analytical and problem-solving skills
- Ability to communicate technical concepts to both technical and non-technical audiences
- Curious, self-motivated, and excited about learning new technologies
Desired Qualifications
- Experience with Microsoft Fabric, including Lakehouse, Warehouse, Notebooks, Real-Time Analytics, and AI workloads
- Familiarity with agentic AI, workflow orchestration, or intelligent automation platforms
- Experience supporting enterprise data platforms in regulated or security-conscious environments
- Knowledge of modern data architecture, including ELT, semantic layers, governance, and data lineage
- Experience working in large, multi-company, or distributed enterprise environments
- A customer-first mindset with the ability to build strong relationships across the business
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