<p>We are seeking a <strong>Senior Data Engineer</strong> to join a growing data and analytics team responsible for building modern, cloud-based data platforms that drive business intelligence, reporting, and advanced analytics. This role is ideal for someone with deep expertise in <strong>Microsoft Azure</strong>, <strong>Microsoft Fabric</strong>, and modern data engineering practices.</p><p>You will be responsible for designing and developing scalable data solutions, optimizing data pipelines, and helping shape the organization's data architecture strategy. The ideal candidate is both hands-on and strategic, with experience building enterprise data platforms in Azure and Fabric environments.</p><p>Responsibilities</p><ul><li>Design, develop, and maintain enterprise data solutions using <strong>Microsoft Fabric</strong> and <strong>Azure Data Services</strong>.</li><li>Build and optimize scalable ETL/ELT pipelines for structured and unstructured data sources.</li><li>Develop and manage data lakes, lakehouses, warehouses, and semantic models.</li><li>Design data integration solutions using Fabric Data Factory, Dataflows, and Azure Data Factory.</li><li>Implement data governance, security, quality, and monitoring frameworks.</li><li>Partner with business stakeholders to understand reporting and analytics requirements.</li><li>Support Power BI developers by building trusted, high-quality data models and datasets.</li><li>Optimize data storage, query performance, and platform scalability.</li><li>Develop data architecture standards, best practices, and documentation.</li><li>Collaborate with application development teams to integrate operational systems with enterprise analytics platforms.</li><li>Support real-time and batch data processing initiatives.</li><li>Participate in architecture reviews, code reviews, and technical leadership activities.</li></ul><p><br></p>
We are looking for a Data Engineer to join our team in Jacksonville, Florida and help shape scalable, enterprise-ready analytics solutions. In this role, you will turn complex business needs into well-structured data models, high-performing pipelines, and actionable reporting assets that support informed decision-making. The ideal candidate brings deep experience with modern data platforms, strong technical leadership, and the ability to guide best practices for analytics, governance, and data usability across the organization.<br><br>Responsibilities:<br>• Design and maintain scalable data pipelines and transformation workflows using tools such as Python, Apache Spark, Hadoop, Kafka, and ETL frameworks.<br>• Build and optimize enterprise semantic models that support consistent metrics, reusable analytics assets, and reliable reporting across multiple business areas.<br>• Partner with business and technical stakeholders to convert complex requirements into practical data solutions, dashboards, and analytical datasets.<br>• Develop and support analytics solutions within modern cloud and hybrid environments, with a strong focus on Microsoft Power BI, Microsoft Fabric, and Azure Synapse Analytics.<br>• Improve data quality, model performance, and platform reliability through testing, validation, tuning, and adherence to established governance standards.<br>• Provide technical guidance to team members by sharing best practices in data modeling, visualization, and scalable analytics design.<br>• Evaluate and incorporate AI-enabled analytics capabilities and automation opportunities while ensuring outputs align with business needs and quality expectations.<br>• Communicate technical concepts and analytical insights clearly to a range of audiences, including leadership, to support strategic decisions.
We are looking for a Data Engineer to build and enhance scalable data solutions that support analytics and business decision-making in Jacksonville, Florida. This role focuses on designing reliable warehouse structures, developing efficient data pipelines, and improving data quality across enterprise platforms. The ideal candidate brings strong technical depth in modern data engineering practices and is comfortable partnering with cross-functional teams to deliver well-governed, high-performing data assets.<br><br>Responsibilities:<br>• Design and maintain enterprise data warehouse solutions using dimensional modeling techniques that support reporting, analytics, and long-term scalability.<br>• Develop, orchestrate, and optimize ETL and ELT workflows for batch and near real-time data movement using modern pipeline and scheduling tools.<br>• Build robust data architectures across cloud-based platforms while balancing performance, resilience, and cost efficiency.<br>• Troubleshoot pipeline failures, data inconsistencies, and performance bottlenecks, then implement practical fixes that improve reliability and throughput.<br>• Apply governance standards by supporting data quality controls, metadata practices, lineage visibility, and role-based access management.<br>• Partner with business and technical stakeholders to translate data needs into well-structured solutions and provide clear updates on progress, risks, and delivery timelines.<br>• Create efficient code for data transformation and aggregation using Python and advanced query development techniques.<br>• Integrate data from databases, APIs, streaming platforms, and external sources to support a broad range of analytical use cases.<br>• Mentor team members and contribute ideas that streamline processes, reduce friction, and strengthen engineering best practices.
<p>Our client is seeking a Data Warehouse Engineer to support the design, development, and optimization of modern enterprise data platforms. This position will play a key role in building scalable data solutions for reporting, analytics, and business intelligence initiatives.</p><p>Responsibilities</p><ul><li>Design and develop ETL/ELT pipelines</li><li>Build and maintain enterprise data warehouses and data marts</li><li>Optimize SQL queries and data models for performance</li><li>Work with business stakeholders to deliver reporting solutions</li><li>Support Power BI, Tableau, or similar analytics platforms</li><li>Ensure data quality, integrity, and governance standards</li></ul><p><br></p>