Job Description: Design, develop, and maintain scalable data pipelines using Azure Databricks and Microsoft Fabric. Implement medallion architecture to support structured data processing through Bronze, Silver, and Gold layers. Build real-time and batch ingestion processes, ensure data quality, and apply transformation logic using Python, Spark, and SQL. Integrate Databricks with Azure services such as OneLake and ADLS Gen2. Collaborate on dimensional and real-time data models, ensure analytics-ready datasets for reporting tools, and standardize schema definitions. Apply governance frameworks with data classification, row-level security, data masking, and integration with Microsoft Purview. Partner with BI developers to optimize datasets for Power BI and create dashboards. Support CI/CD pipelines, performance tuning, and job monitoring. Requirement/Must Have: Proficiency in advanced SQL for data transformation and optimization Hands-on experience with: Azure Databricks (Spark, Delta Lake). Microsoft Fabric (Dataflows, Pipelines, OneLake). SQL and Python (Pandas, PySpark). SQL Server 2019+. Understanding of ETL/ELT processes and data quality standards. Experience with dimensional and real-time data modeling. Familiarity with data governance and security best practices. Experience: 3+ years in data engineering or analytics engineering roles. Responsibilities: Build and maintain ETL/ELT pipelines using Azure Databricks and Microsoft Fabric. Implement medallion architecture and Delta Lake capabilities. Develop real-time and batch data ingestion processes. Integrate with Azure services and support Microsoft Purview for metadata management. Design dimensional models and analytics-ready datasets for Power BI. Apply data classification, security policies, and compliance standards. Create dashboards and train users in reporting tools. Support CI/CD workflows and optimize cluster performance. Should Have: Experience with Power BI datasets and semantic modeling. Knowledge of Microsoft Purview, Unity Catalog, or similar governance tools. Exposure to real-time processing and streaming architectures. Understanding of federal/state compliance requirements for data. Skills: Strong analytical and problem-solving abilities. Excellent communication skills for both technical and non-technical audiences Ability to collaborate with government stakeholders. Qualification And Education: Bachelor’s degree in Computer Science, Data Engineering, or a related field. Microsoft Fabric Analytics Engineer certification (preferred).