Job Summary: We are seeking a professional with architectural vision, analytical capability, and autonomy to work on data engineering and Microsoft Fabric. Key Highlights: 1. Experience with Microsoft Fabric, Lakehouse, and Data Pipelines 2. Advanced knowledge of SQL, Python, and PySpark 3. Focus on data governance, security, and optimization **Behavioral Profile:** Architectural Vision, Communication with Business Areas, Autonomy, Analytical Capability, Continuous Learning. Desirable certifications: DP\-600 – Fabric Analytics Engineer and DP\-203 – Data Engineering on Azure. **Requirements:** Topic Subtopics / Expected Knowledge 1\. Data Engineering Fundamentals Relational modeling Dimensional modeling (Star / Snowflake) Data Warehouse concepts Data Lake concepts Lakehouse architecture Normalization vs. Denormalization Partitioning and performance 2\. Databases and SQL Advanced SQL Complex joins Window Functions CTEs Query optimization Experience with SQL Server / Azure SQL / Synapse 3\. ETL / ELT and Data Pipelines ETL and ELT concepts in Alteryx Data ingestion Data transformation Incremental loading CDC (Change Data Capture) Error handling and reprocessing Data quality and validation 4\. Microsoft Fabric – Architecture Fabric as SaaS concept OneLake Fabric multiexperience Difference between Lakehouse, Warehouse, and KQL Database 5\. Microsoft Fabric – Lakehouse Lakehouse creation and management Use of Delta Lake Schema control Data versioning Bronze / Silver / Gold architecture 6\. Microsoft Fabric – Data Pipelines (Data Factory) Visual pipeline creation Copy Activity Parameters Triggers and scheduling Integration with SQL, APIs, and files Pipeline monitoring 7\. Microsoft Fabric – Notebooks (Spark) Notebook usage in Fabric PySpark Spark SQL Distributed transformations Joins and Window Functions in Spark Spark job optimization 8\. Programming Languages SQL (mandatory) Python PySpark Scala (preferred) 9\. Power BI Integration Direct Lake Semantic modeling Refresh and Incremental Refresh Basic DAX concepts Security (RLS) 10\. Governance and Security Access control in Fabric Workspace-level permissions Microsoft Purview concepts Data governance LGPD (conceptual) 11\. Observability and Operations Load monitoring Troubleshooting Failure management Fabric capacity consumption (F\-SKU) Costs and performance 12\. Azure Knowledge (Complementary) Azure Data Lake Gen2 Azure Synapse (conceptual) Azure DevOps / Git Code versioning CI/CD for data (preferred) Benefits CLT Global