Data Engineering

You will validate data loads and transformations within complex big data pipelines and cloud infrastructures. Responsibilities Validate source and target data loads using complex SQL scripting across Oracle, AWS Redshift, and MS SQL Server. Test big data pipelines using Hadoop and Spark frameworks within AWS cloud environments. Execute various testing methodologies including functional, system integration, end-to-end, regression, and user acceptance testing. Perform load, performance, and stress testing as required. Manage test cases and defect tracking using JIRA and Excel within Agile Scrum environments. Participate in defect triaging during major releases to ensure resolution. Required Skills 5+ years of experience in data engineering or testing roles. Proficiency in complex SQL scripting for data validation. Experience with Oracle, AWS Redshift, and MS SQL Server. Hands-on experience with Hadoop and Spark frameworks. Practical knowledge of Spark DataFrame API and PySpark for data manipulation. Deep understanding of ETL processing, data warehousing, and business intelligence architecture. Strong grasp of SDLC and STLC processes in Agile environments. Expertise in JIRA for defect management. Preferred Skills Python scripting for automated test creation. Experience with TOSCA automation tools. Functional knowledge of Salesforce CRM or Oracle Eloqua.