Full/Part Time:Full-Time / Hybrid 2 days on site
Compensation:$76,296.54- $ 114,444.82
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
Responsibilities
- 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 OneLake, 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.
Experience
- 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 (OneLake, 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.
Requirements
Knowledge
- 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.
Skills
- 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 and receive work direction.