Lead II - Software Testing (ETL Testing+Python)

Job Title: Data QA Lead Job Summary We are seeking an experienced Data QA Lead to drive data quality initiatives and ensure the accuracy, integrity, consistency, and reliability of enterprise data. The ideal candidate will lead data quality validation efforts, mentor QA analysts, establish data quality standards, and implement automation frameworks to support business-critical, data-driven decision-making. Key Responsibilities Lead and oversee data quality assurance activities across multiple data sources and platforms. Define, implement, and enforce data quality standards, processes, and best practices. Design and execute data validation, reconciliation, and integrity checks to ensure data accuracy and consistency. Utilize SQL, Excel, and Python to analyze, validate, and automate data quality processes. Develop and maintain automated data quality testing frameworks and monitoring solutions. Identify data anomalies, trends, patterns, and root causes of data issues. Collaborate with data engineering, business, and analytics teams to resolve data quality defects and improve data reliability. Review and approve data quality reports, dashboards, and metrics. Drive continuous improvement initiatives for data governance and quality management. Mentor and guide junior Data QA Analysts, providing technical leadership and best practice recommendations. Participate in project planning, risk assessment, and quality reviews for data-related initiatives. Ensure timely documentation of data quality findings, resolutions, and process improvements. Required Skills & Qualifications 7-10 years of experience in Data Quality Assurance, Data Validation, Data Analysis, or Data Management. Strong expertise in SQL for complex querying, data validation, and troubleshooting. Advanced proficiency in Microsoft Excel for data analysis and reporting. Strong hands-on experience with Python for automation, scripting, and data quality checks. Experience in designing and implementing automated data testing frameworks. Knowledge of data warehousing, ETL processes, and data lifecycle management. Strong analytical, problem-solving, and root cause analysis skills. Excellent communication and stakeholder management abilities. Experience leading teams and mentoring analysts. Familiarity with data governance, data quality metrics, and industry best practices. Preferred Qualifications Experience with BI and analytics tools such as Power BI, Tableau, or similar platforms. Exposure to cloud data platforms such as Azure, AWS, or GCP. Knowledge of data governance and master data management concepts. Relevant certifications in Data Management, SQL, Python, or Cloud Technologies are a plus.