
Senior Data Quality Assurance Specialist
6 days ago
We are seeking a detail-oriented Data Quality Assurance Specialist to ensure the quality and accuracy of data migration projects. The ideal candidate will be responsible for validating data integrity, testing migration processes, and identifying discrepancies or issues. This role requires expertise in QA methodologies, strong analytical skills, and familiarity with data migration processes and tools.
Key Responsibilities:
- Data Validation and Testing: Develop and execute comprehensive test plans and test cases to validate data migration processes.
- Ensure Data Integrity, Accuracy, and Consistency across source and target systems.
- Perform Pre- and Post-Migration Data Checks to verify successful migration.
- Test Automation: Design and implement automated test scripts for data validation and reconciliation.
- Use Appropriate Tools to streamline testing processes and reduce manual effort.
- Defect Identification and Resolution: Identify, document, and report issues or discrepancies in the data migration process.
- Collaboration and Communication: Work closely with data engineers, business analysts, and stakeholders to understand migration requirements and objectives.
- Process Improvement: Recommend and implement best practices for data migration testing and validation.
Requirements:
- Bachelors degree in Computer Science, Information Technology, or a related field.
- 3+ years of experience in quality assurance or data testing, preferably in data migration projects.
- Strong knowledge of SQL for querying and validating data.
- Familiarity with data migration tools and ETL processes (e.g., Informatica, Talend, or similar).
- Hands-on experience with test automation tools (e.g., Selenium, TestNG, or similar).
- Understanding of data governance, privacy, and security principles.
- Strong analytical skills with attention to detail.
- Excellent communication and collaboration abilities.
Preferred Qualifications:
Experience with cloud-based data migration (e.g., AWS, Azure, GCP). Familiarity with big data frameworks and tools (e.g., Hadoop, Spark). Knowledge of Agile methodologies and tools like Jira or Confluence.
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