Data Engineer

Kforce has a client that is seeking a Data Engineer in Orlando, FL. Summary: The Data Engineer designs, builds, and maintains scalable data pipelines and modern data platforms that transform enterprise data into trusted, actionable information for analytics and decision-making. Leveraging Microsoft Fabric (Data Factory, OneLake, and Data Warehouse/Lakehouse), this role integrates and prepares data from diverse sources into governed, high-quality datasets. Working closely with analysts, BI developers, and business stakeholders, the Data Engineer ensures data is reliable, secure, and optimized for self-service analytics (e.g., Power BI), enabling consistent reporting and data-driven insights. Duties and Responsibilities:

• Design, implement, and optimize end-to-end data pipelines to ingest, transform (ETL/ELT), and integrate data from multiple source systems into a centralized OneLake data lake and Fabric data warehouse/lakehouse, leveraging Microsoft Fabric's Data Factory and Data
• Build repeatable, scalable workflows (using pipelines, dataflows, and notebooks) that deliver timely and accurate data for analytics
• Integrate data from enterprise and airport operational systems, including business applications, infrastructure platforms, security systems, facilities systems, financial systems, asset management tools, and other airport technology platforms, to support enterprise reporting, operational intelligence, performance measurement, and modernization initiatives
• Bachelor's degree in Computer Science, Data Engineering, Data Analytics, Computer Science, Statistics, related field with demonstrated expertise with relevant industry in data engineering, data integration, or analytics engineering or an equivalent combination of (10)+ years education, training and management experience
• Hands-on experience developing ETL/ELT pipelines and working with data integration frameworks
• Experience with data lake storage (e.g., Azure Data Lake, S3) and big data processing (e.g., Apache)
• Experience building or using data warehouses/lakehouses for large-scale analytics (e.g., Azure Synapse, Snowflake, BigQuery, or Microsoft Fabric Data Warehouse)
• Strong understanding of relational and dimensional data modeling principles
• Familiarity with orchestration tools (e.g., Azure Data Factory, Fabric Data Factory pipelines, or similar ETL tools) and ability to work with APIs, databases, and flat files for data ingestion
• Knowledge of Fabric's core components (Data Factory, Data Engineering, Lakehouse, Data Warehouse, etc.) and their integration with Power BI is strongly preferred
• Proficiency in SQL for data transformation and querying, and in a programming language (Python, Scala, or similar) for complex data processing tasks
• Proficiency in cloud data platforms and services - especially Microsoft Azure and Microsoft Fabric - or comparable cloud-based data ecosystems
• Ability to design efficient database schemas and optimize SQL queries for performance