> Markdown version of [/jobs/ext/4636696-data-analytics-ai-engineer](https://www.wearedevelopers.com/jobs/ext/4636696-data-analytics-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data, Analytics & AI Engineer - **Company:** DEPLOY, LLC - **Location:** Birmingham, AL, United States - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Computer Programming, Databases, Data Architecture, Information Engineering, Relational Databases, DevOps, Python (Programming Language), Machine Learning, SQL Azure, Raw Data, Power BI, Standard Sql, Azure Machine Learning, Workflow Management Systems, Enterprise Data Management, Azure Data Factory, Boomi, Agentic-AI, Data Layers, Microsoft Fabric, Information Technology, Data Lineage, Integration Frameworks, Stream Analytics, Data Pipelines - **Published:** November 8, 2026 - **Apply:** https://www.juju.com/job/16_d59b84444 ## About the Role 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. Bonus Points If You Have 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. ## Description Design, build, and maintain scalable data pipelines using Azure Data Factory and Boomi. Integrate data from ERP, EHS, operational, and enterprise systems. Develop and manage curated data models in Azure SQL while helping migrate to Microsoft Fabric Lakehouse and Warehouse architectures. Ensure high levels of data quality, performance, governance, and reliability. Help establish best practices and architecture standards for the next generation data platform. Deliver Powerful Analytics Build interactive dashboards, semantic models, and reports using Power BI. Partner with business leaders to translate business questions into actionable KPIs and analytics. Enable self-service reporting through well-designed datasets and documentation. Turn raw data into meaningful business insights. Drive AI Innovation Design, prototype, and deploy AI and Machine Learning solutions. Build intelligent workflows that automate multi-step business processes using AI and agentic technologies. Leverage Azure AI services and Microsoft Fabric capabilities including notebooks, machine learning, and real-time analytics. Champion responsible AI adoption across the organization. Identify opportunities where AI can improve forecasting, anomaly detection, classification, automation, and decision-making. Collaborate Across the Business Partner with IT, Security, DevOps, and business leaders to deliver secure, scalable solutions. Work closely with cross-functional teams and affiliate companies on strategic initiatives. Manage projects with measurable business outcomes and clear success metrics. Innovate Continuously Evaluate emerging technologies in data, analytics, and AI. Recommend improvements that create measurable business value.