Senior Azure Data Engineer

Wissen Technology is hiring for Senior Azure Data Engineer <\/span>
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About Wissen Technology: <\/b> <\/span>
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At Wissen Technology, we deliver niche, custom\-built products that solve complex business challenges across industries worldwide. Founded in 2015, our core philosophy is built around a strong product engineering mindset\u2014ensuring every solution is architected and delivered right the first time. Today, Wissen Technology has a global footprint with 2000+ employees across offices in the US, UK, UAE, India, and Australia. Our commitment to excellence translates into delivering 2X impact compared to traditional service providers. How do we achieve this? Through a combination of deep domain knowledge, cutting\-edge technology expertise, and a relentless focus on quality. We don\u2019t just meet expectations\u2014we exceed them by ensuring faster time\-to\-market, reduced rework, and greater alignment with client objectives. We have a proven track record of building mission\-critical systems across industries, including financial services, healthcare, retail, manufacturing, and more. Wissen stands apart through its unique delivery models. Our outcome\-based projects ensure predictable costs and timelines, while our agile pods provide clients with the flexibility to adapt to their evolving business needs. Wissen leverages its thought leadership and technology prowess to drive superior business outcomes. Our success is powered by top\-tier talent. Our mission is clear: to be the partner of choice for building world\-class custom products that deliver exceptional impact\u2014the first time, every time. <\/span>
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Job Summary: <\/b> <\/span>
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We are seeking a highly skilled Senior Azure Data Engineer to design, develop, and optimize enterprise\-scale data platforms on Microsoft Azure. The ideal candidate should have strong hands\-on experience in Azure Data Engineering, Databricks, PySpark, and modern lakehouse architectures. <\/span>
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Experience<\/b>: 7 to 12 Years <\/span>
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Location<\/b>: Bangalore <\/span>
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Mode of Work<\/b>: Full Time | 5 Days WFO <\/span>
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Key Responsibilities \- <\/b> <\/span>
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• Design and develop scalable data pipelines using Azure Data Factory, Azure Databricks, and PySpark. <\/span>
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• Build and maintain lakehouse architecture using Azure Data Lake Storage Gen2 and Delta Lake. <\/span>
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• Develop ETL/ELT frameworks for large\-scale data processing. <\/span>
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• Optimize Spark workloads for performance, reliability, and cost efficiency. <\/span>
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• Implement data quality, governance, security, and monitoring best practices. <\/span>
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• Collaborate with business stakeholders, analysts, and engineering teams to deliver data solutions. <\/span>
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• Drive CI/CD implementation and automation for data engineering workflows. <\/span>
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• Troubleshoot production issues and ensure platform stability. <\/span>
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  Required Skills & Qualifications:<\/b> <\/span>
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  • Strong experience with Azure Databricks <\/span>
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  • Hands\-on expertise in PySpark <\/span>
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  • Azure Data Factory (ADF) <\/span>
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  • Azure Data Lake Storage (ADLS Gen2) <\/span>
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  • Delta Lake <\/span>
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  • Azure Synapse Analytics <\/span>
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  • Advanced SQL and Python <\/span>
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  • Data Modelling and Lakehouse Architecture <\/span>
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  • CI/CD and Git\-based development <\/span>
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    Must Have Skills:<\/b> <\/span>
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    • Azure Databricks <\/span>
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    • PySpark <\/span>
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    • Azure Data Factory <\/span>
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    • ADLS Gen2 <\/span>
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    • SQL <\/span>
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    • Python <\/span>
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    • Data Engineering Architecture <\/span>
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    • ETL/ELT Development <\/span>
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      Good To Have Skills:<\/b> <\/span>
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      • Microsoft Fabric <\/span>
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      • Azure Event Hub <\/span>
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      • Kafka <\/span>
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      • Azure ML <\/span>
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      • Terraform <\/span>
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      • Power BI <\/span>
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      • Databricks Workflows <\/span>
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        Soft Skills:<\/b> <\/span>
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        • Strong communication skills <\/span>
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        • Ownership mindset <\/span>
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        • Problem\-solving ability <\/span>
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        • Stakeholder management <\/span>
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        • Collaborative team player <\/span>
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          Wissen Sites:<\/b> <\/span>
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          Website: <\/span>www.wissen.com<\/span><\/span><\/a>
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          LinkedIn: <\/span>https://www.linkedin.com/company/wissen\-technology<\/span><\/span><\/a> <\/span>
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          Wissen Leadership: <\/span>https://www.wissen.com/company/leadership\-team/<\/span><\/span><\/a> <\/span>
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          Wissen Live: <\/span>https://www.linkedin.com/company/wissen\-technology/posts/feedView=All<\/span><\/span><\/a> <\/span>
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          Wissen Thought Leadership: <\/span>https://www.wissen.com/articles/<\/span><\/span><\/a> <\/span>
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