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Wissen Technology is hiring for Senior Azure Data Engineer. About Wissen Technology: 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—ensuring 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’t just meet expectations—we 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—the first time, every time. Job Summary: 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.
Job Responsibility
Design and develop scalable data pipelines using Azure Data Factory, Azure Databricks, and PySpark
Build and maintain lakehouse architecture using Azure Data Lake Storage Gen2 and Delta Lake
Develop ETL/ELT frameworks for large-scale data processing
Optimize Spark workloads for performance, reliability, and cost efficiency
Implement data quality, governance, security, and monitoring best practices
Collaborate with business stakeholders, analysts, and engineering teams to deliver data solutions
Drive CI/CD implementation and automation for data engineering workflows
Troubleshoot production issues and ensure platform stability