2-3 years of experience in Data Engineering and Azure Data Platform. Strong hands-on experience with Azure Data Factory (ADF). Experience with Azure Data Lake Storage (ADLS Gen2). Strong SQL development skills, including query optimization and performance tuning. Experience in designing and maintaining ETL/ELT pipelines. Knowledge of Azure SQL Database, Synapse Analytics, or SQL Server. Understanding of data warehousing concepts and dimensional data modeling. Experience with source control tools such as Git/Azure DevOps. Familiarity with data integration patterns and cloud-based data architectures. Strong analytical and problem-solving skills.
Design, develop, and maintain end-to-end data ingestion and transformation pipelines using Azure Data Factory (ADF). Build and optimize ETL/ELT workflows for processing large volumes of structured and unstructured data. Integrate data from multiple on-premises and cloud-based sources into enterprise data platforms. Develop and maintain Azure Data Lake Storage (ADLS) based data solutions. Monitor, troubleshoot, and optimize ADF pipelines to ensure reliability and performance. Collaborate with business stakeholders to gather requirements and translate them into scalable technical solutions. Implement data quality checks, validation mechanisms, and monitoring frameworks. Create reusable components, technical documentation, and best practices for data engineering projects. Support production deployments, issue resolution, and continuous improvement initiatives. Participate in code reviews and contribute to data architecture and design discussions.
Infosys Data & Analytics practice helps global enterprises accelerate their digital transformation through cloud, AI, advanced analytics, and modern data platforms. As an Azure Data Engineer, you will work on enterprise-scale data modernization initiatives involving cloud migration, data lake implementation, real-time analytics, and AI-ready data platforms.
