Job description

Hello There, My name is Himanshu Sharma, and I serve as the Recruitment Lead at Kanak-IT INC. I am reaching out to share an excellent career opportunity for the role of Azure Data Engineer with our esteemed client. If you are interested then please share your updated resume at Himanshu01@kanakits.com Job Description Position : Azure Data Engineer Location : Roswell, GA Hybrid/Remote Duration : Long term contract Description The client is transitioning into Microsoft Fabric, and this role will play a key part in that journey. The Data Engineer will be responsible for building and maintaining end-to-end data pipelines for analytics solutions, leveraging Microsoft Azure Cloud, Azure Synapse Analytics, and Microsoft Fabric. Qualifications (Must-Have) • Minimum of 8 10 years of hands-on experience building data pipelines, data models, and supporting enterprise data warehouse solutions. • Hands-on experience with Microsoft Fabric for data pipelines, modeling, and analytics. • Proficiency with Microsoft Azure data services, including Azure Synapse Analytics. • Strong SQL, data modeling, and ETL/ELT development skills. • Experience working within a scaled agile framework for data engineering product delivery. • Microsoft Azure certifications in analytics technologies are a plus. • 4+ years of experience with ETL and cloud data technologies, including Azure Data Lake, Azure Data Factory, Azure Synapse, Azure Logic Apps, Azure Functions, Azure Data Explorer, and Power BI (or equivalent platforms). • 4+ years of experience in big data scripting languages such as Python, SCOPE, or SQL. • 4+ years of experience in one scripting language for data retrieval and manipulation (e.g., SQL or KQL). Responsibilities • Build and maintain end-to-end data pipelines across Azure Synapse Analytics and Microsoft Fabric. • Develop and implement solutions on the Azure cloud platform to support a modern enterprise data platform. • Partner with cross-functional teams to ensure data is collected, stored, processed, and analyzed in a timely, efficient, and accurate manner. • Design, develop, and implement analytics solutions on Azure Synapse Analytics. • Develop ETL/ELT processes for large-scale data ingestion, ensuring data quality and pipeline performance. • Transform and model data to meet business requirements, loading it into Azure Synapse SQL Warehouse/Azure Data Lake Storage. • Implement monitoring and error handling processes for reliable data integration. • Optimize pipelines for cost and performance through query tuning, caching, and resource management. • Automate repeatable data preparation tasks to reduce manual processes. • Collaborate with data governance, cloud service providers, visualization, and IT/business teams to deliver analytics solutions. • Provide troubleshooting, analysis, and production support for existing solutions, including enhancements. Skills • Strong SQL, data modeling, data warehouse, and OLAP concepts. • Experience with Azure Data Lake Storage, Azure Synapse Analytics, Azure Spark Pools, Databricks Notebook, Cosmos DB, CDC tools, Python, DevOps, and CI/CD. • Familiarity with data integration tools (e.g., Qlik Replicate) and data modeling tools (e.g., Erwin) is a plus. • Familiarity with data lake medallion architecture and unified data models. • Familiarity with contextualization products (e.g., Cognite) is a plus. • Experience with visualization tools such as Microsoft Power BI and Tableau. • Familiarity with Scaled Agile, DevOps, Scrum, and ITIL concepts. • Experience with Microsoft SSIS, SSRS, and SSAS is a plus. Competencies • Strong communication and presentation skills, able to engage with technical and non-technical stakeholders across IT and business teams. • Collaboration & Building Partnerships Skilled at developing and leveraging relationships across groups to deliver results. • Drive for Results Takes ownership and proactively acts to achieve objectives and goals. • Continuous Improvement Identifies opportunities, generates ideas, and implements solutions to improve processes and conditions.

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