Data Quality Engineer (Data Testing) STA

We are looking for an enthusiastic and self-motivated Quality Assurance Analyst who is passionate about ensuring software/data service quality, a person who can work on QA principles and testing methodologies focused on data quality assurance. This new position is a hundred percent hands-on and full time. Responsibilities: • Validate data accuracy, completeness, and integrity before its utilization. • Automate and execute test cases for data layer validation and ETL jobs. • Utilize AWS Athena and Python tools for data querying and validation. • Collaborate with stakeholders to resolve data-related issues. • Ensure dashboards and reports align with business requirements. • Create and maintain detailed test documentation. • Identify and resolve data discrepancies while ensuring seamless updates through regression testing. Requirement: • Strong knowledge of QA principles and testing methodologies focused on data quality assurance. • Create and maintain detailed test plans, test cases, and documentation for data testing activities. • Expertise in data testing, validation techniques, and troubleshooting discrepancies. • Proficiency in Python or any other scripting language for automating test cases and data validations. • Automate data validation processes using Python and other relevant tools. • Hands-on experience with databases (e.g., MySQL, PostgreSQL, MongoDB) and writing complex SQL queries. • Knowledge of AWS Athena, S3 buckets for querying and validating data in cloud-based data lakes. • Experience with testing different ETL jobs, including both manual and automated frameworks. • Validate dashboards and reports to ensure accuracy and alignment with business requirements. • Identify, report, and track discrepancies or anomalies in data to closure. • Familiarity with API testing workflows and dashboard validation. • Strong analytical and problem-solving skills with attention to detail. • Collaborate with developers, data engineers, and stakeholders to resolve data-related issues effectively. Desired Skills: • Experience with tools like Pytest, Pandas, or PySpark for data validation and processing. • Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and big data technologies like Hadoop and Spark. • Knowledge of CI/CD pipelines and their role in testing processes. • Exposure to dashboard testing for accurate data visualization.