Consultant / Sr Consultant - Qa Data Engineer Job in Fresh Gravity Software Services

Requirements Responsibilities: Collaborate with data engineers to understand data engineering requirements and design specifications. Develop and execute comprehensive test plans, test cases, and test scripts to validate data engineering workflows, ETL (Extract, Transform, Load) processes, and data integration pipelines. Perform manual and automated testing on data engineering solutions to identify data quality issues, data inconsistencies, and data integrity problems. Verify data transformations, data mappings, and data aggregations to ensure accuracy and adherence to business rules and data governance standards. Conduct performance testing to evaluate the scalability, efficiency, and responsiveness of data engineering systems under different load conditions. Document and report software defects, bugs, and anomalies in the data engineering processes, and collaborate with the development team to track issues to resolution. Collaborate with cross-functional teams, including data scientists, business analysts, and stakeholders, to understand data requirements and ensure data engineering solutions meet the specified criteria. Continuously improve QA processes, tools, and methodologies to enhance the efficiency and effectiveness of data engineering testing activities. Stay up-to-date with emerging technologies, industry trends, and best practices in data engineering and quality assurance. Qualifications: Bachelor's degree in Computer Science, Engineering, Data Science, or a related field. Proven experience in data engineering, data quality assurance, or a similar role. Strong knowledge of data management concepts, database systems, and ETL processes. Proficiency in SQL for data querying and validation. Familiarity with programming languages such as Python, Java, or Scala for test automation and scripting. Experience with data quality frameworks, data profiling, and data validation techniques. Hands-on experience with data engineering tools and technologies, such as Apache Spark, Hadoop, SQL-based databases, and data integration platforms. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data services. Excellent analytical and problem-solving skills. Strong attention to detail and ability to prioritize tasks in a fast-paced environment. Effective communication and collaboration skills to work with cross-functional teams. Certifications in quality assurance, data engineering, or related fields (optional).