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.
Responsibilities:
- Design and maintain scalable data pipelines and transformation workflows using tools such as Python, Apache Spark, Hadoop, Kafka, and ETL frameworks.
- Build and optimize enterprise semantic models that support consistent metrics, reusable analytics assets, and reliable reporting across multiple business areas.
- Partner with business and technical stakeholders to convert complex requirements into practical data solutions, dashboards, and analytical datasets.
- 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.
- Improve data quality, model performance, and platform reliability through testing, validation, tuning, and adherence to established governance standards.
- Provide technical guidance to team members by sharing best practices in data modeling, visualization, and scalable analytics design.
- Evaluate and incorporate AI-enabled analytics capabilities and automation opportunities while ensuring outputs align with business needs and quality expectations.
- Communicate technical concepts and analytical insights clearly to a range of audiences, including leadership, to support strategic decisions.
- Bachelor’s degree in Information Systems, Computer Science, Data Analytics, Business, or a related discipline, or equivalent practical experience.
- 7+ years of experience in analytics, business intelligence, data engineering, or data modeling roles.
- Proven ability to translate complex business problems into enterprise-level analytical and data solutions.
- Strong expertise in data modeling concepts such as dimensional design, metric definition, granularity, and scalable semantic layer development.
- Hands-on experience with modern data platforms, including cloud data warehouses, lakehouse environments, or hybrid data architectures.
- Advanced technical proficiency with Python, Apache Spark, Hadoop, Kafka, ETL processes, and data querying or transformation languages.
- Demonstrated experience with Microsoft Power BI, Microsoft Fabric, and Azure Synapse Analytics.
- Experience leading or mentoring technical team members and promoting analytics standards, governance, and adoption across an organization.