Cloud Data Architect Specialist

Há 3 dias


Fortaleza CE, Brasil beBeeDataEngineer Tempo inteiro

Job Title Azure Data Engineer responsible for designing and implementing end-to-end data architecture solutions on Microsoft Azure. This role involves developing and managing ETL/ELT pipelines using Azure Data Factory, architecting and optimizing Data Lake storage solutions for structured and unstructured data, leveraging Azure Databricks for big data processing, analytics, and machine learning workflows, integrating Azure Machine Learning models into data pipelines and business applications, and designing and maintaining Azure SQL databases to ensure performance, scalability, and security. This is an exciting opportunity for a professional with strong proficiency in Azure Foundry, Data Factory, Data Lake, Databricks, and Azure SQL, as well as experience with Microsoft Fabric and its integration into enterprise data platforms, a solid understanding of machine learning concepts and deployment in Azure ML, expertise in data modeling, data warehousing, and data governance, and familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code. Key Responsibilities Design and implement end-to-end data architecture solutions on Microsoft Azure. Develop and manage ETL/ELT pipelines using Azure Data Factory. Architect and optimize Data Lake storage solutions for structured and unstructured data. Leverage Azure Databricks for big data processing, analytics, and machine learning workflows. Integrate Azure Machine Learning models into data pipelines and business applications. Design and maintain Azure SQL databases ensuring performance, scalability, and security. Required Skills & Qualifications Professional English written and oral communication. Proven experience as a Data Architect or similar role in a cloud-first environment. Strong proficiency in Azure Foundry, Data Factory, Data Lake, Databricks, and Azure SQL. Experience with Microsoft Fabric and its integration into enterprise data platforms. Solid understanding of machine learning concepts and deployment in Azure ML. Expertise in data modeling, data warehousing, and data governance. Familiarity with DevOps practices, CI/CD pipelines, and infrastructure-as-code.


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