Data Engineer

Description

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.

Requirements

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.

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