SQL Data

Data Modeler- Insurance We are currently hiring for a Data Modeler with Azure Synapse Analytics experience to join one of our Insurance clients on a 6 month contracts. Remote Develop, maintain, and optimize semantic data models using Azure Synapse Analytics. Design data models that integrate data from Azure Data Lake Storage Gen2, Azure SQL databases, and other sources for consumption in Power BI and Synapse SQL pools. Ensure data model accuracy, scalability, and performance. Use PySpark within Azure Synapse notebooks to extract, transform, and load (ETL/ELT) data from raw formats (e.g., Integrate data from Azure SQL databases and other sources into unified data models for analytical use. Implement data transformation pipelines and workflows in PySpark. Partner with DevOps teams to deploy and maintain data models in production environments. Optimizing data models from various sources such as Azure SQL databases and Azure Data Lake Storage Gen2 for usage in Power BI Ensure efficient querying of large datasets and troubleshoot any performance issues related to data retrieval or processing. Create and maintain detailed documentation and schematics of data models, metadata, and processes using suitable tools, such as Visio. Develop and enforce data governance and data modeling standards to ensure consistency and accuracy across all models. Ensure all data modeling practices adhere to security and compliance requirements, including role-based access control, encryption, and data privacy laws (e.g., Applying RL/CL/OL security within the data models as defined by business use and target audience Knowledge of machine learning and advanced analytics within the Azure ecosystem (e.g., Familiarity with Data Governance practices in conjunction with Azure Purview (data lineage, data categorization, and data certification) Certifications such as Microsoft Certified: Azure Data Engineer Associate or Microsoft Certified: Experience in data modeling and data engineering roles, with at least 4+ years of experience working with Azure cloud services and big data technologies.