Microsoft Fabric Data Engineer

Full/Part Time:Full-Time / Hybrid 2 days on site

Compensation:$76,296.54- $

Work Authorization: Must be authorized to work in the U.S. without current or future employer sponsorship. This position does not offer H-1B sponsorship or STEM OPT.

The Microsoft Fabric Data Engineer is responsible for designing, building, and maintaining enterprise data engineering solutions on the Microsoft Fabric platform. They develop end-to-end data pipelines, lakehouse and warehouse architectures, and semantic models that transform raw source data into governed, analytics-ready assets. Working closely with business users and analytics teams, they translate requirements into scalable, reliable data solutions that power reporting, dashboards, and downstream analytics across the enterprise.

Location:Clearwater, FL

• Collaborate with the Product Owner, business users, and application development teams to gather requirements and translate them into data engineering solutions.
• Design, develop, and maintain end-to-end data pipelines in Microsoft Fabric using Data Factory pipelines and Dataflows Gen2 to ingest data from diverse source systems.
• Architect and implement Lakehouse and Data Warehouse solutions in One Lake, applying a medallion (bronze/silver/gold) architecture for scalable, reusable data layers.
• Develop data transformation logic using Fabric Notebooks (PySpark / Spark SQL) and T-SQL to cleanse, enrich, and model data.
• Build and optimize semantic models and Power BI datasets, leveraging Direct Lake mode for high-performance analytics.
• Design and implement ETL/ELT processes, data mappings, and data specifications for integration within the enterprise data platform.
• Design and develop database objects (tables, stored procedures, views, etc.) that support data integration and transformation.
• Implement data governance, security, lineage, and quality controls using Microsoft Purview and Fabric's built-in governance capabilities.
• Monitor, tune, and troubleshoot pipeline performance, capacity utilization, and data refresh reliability.
• Establish and manage CI/CD practices using Fabric's Git integration and deployment pipelines to promote content across environments.
• Continuously review data loaded into the platform for accuracy, proposing solutions to improve data quality and processing performance.
• Participate in quality assurance testing and monitor the issue ticketing system.

• Bachelor's degree in a related field.
• Minimum of 5 years of experience across all stages of data engineering / BI project work, including requirement definition, logical design, implementation, testing, and deployment.
• Hands-on experience with the Microsoft Fabric platform (One Lake, Lakehouse, Data Warehouse, Data Factory, Dataflows Gen2, Notebooks, Direct Lake), or equivalent modern data platform experience (e.g., Azure Synapse, Databricks).
• Strong database design and integration experience with SQL Server / Azure SQL, including a solid understanding of relational databases and the SQL language.
• Experience developing ETL/ELT solutions and data pipelines.
• Knowledge of data lakehouse, data warehouse, and dimensional modeling (star/snowflake, medallion architecture) design.
• Proficiency in Python / PySpark for data transformation and processing.
• Experience with data modeling and report development using Microsoft Power BI (DAX, semantic models).
• Familiarity with Azure data services (Azure Data Lake Storage, Azure Synapse, Azure SQL).
• Familiarity with Agile methodologies and working in a shorter release cycle / continuous delivery environment.
• Experience with data governance and cataloging tools (e.g., Microsoft Purview) is desirable.
• Experience in the higher education sector is highly desirable.

• Systems analysis and design principles;
• Data engineering and data warehouse design principles;
• Project management principles;
• Applicable programming and query languages (SQL, Python/PySpark, DAX);
• Process improvement principles;
• ETL/ELT and data integration methods, principles, and practices;
• Data governance, security, and quality principles;
• Cloud data platform concepts;
• Operating systems;
• Customer service principles;
• Training principles;
• Computers and related software applications.

• Programming and troubleshooting data pipelines, databases, and systems;
• Building and managing data engineering solutions on the Microsoft Fabric platform;
• Designing and optimizing lakehouse, warehouse, and semantic models;
• Establishing and following procedural and technical standards;
• Monitoring and assessing data pipelines and platform performance;
• Training end-users on applications and systems;
• Communicating technical information to a non-technical audience;
• Interpreting customer requirements and translating them into system specifications;
• Using a computer and related software applications;
• Communication and interpersonal skills as applied to interaction with subordinates, coworkers, supervisors, the general public, etc., sufficient to exchange or convey information and to give…