QA Lead

Position OverviewWe are seeking a skilled Test Data Engineer with proven experience in RDBMS masking, data obfuscation, and test data management (TDM). The successful candidate will play a key role in delivering secure, consistent, and high-quality test data using the DATPROF IBM Optim, CA Datamaker or similar Test Data Provisioning Suite.Key ResponsibilitiesDesign, implement, and maintain data masking and anonymization solutions for relational databases (e.g., Oracle, SQL Server, PostgreSQL, MySQL).Develop automation frameworks and pipelines to provision masked, synthetic, or subsetted data across test environments.Collaborate with QA, DevOps, and application teams to understand test data requirements and ensure compliance with data privacy standards (e.g., GDPR, HIPAA, PCI DSS).Optimize test data generation, refresh, and masking processes for performance and scalability.Implement RDBMS-level transformations, triggers, and stored procedures to support dynamic masking and subsetting strategies.Ensure data integrity and consistency across masked and subsetted environments.Document best practices, policies, and technical procedures related to test data engineering.Monitor, troubleshoot, and resolve issues related to test data pipelines, masking jobs, and refresh processes.

Required Skills & Experience

7+ years of experience as a Data Engineer, Test Data Engineer, or similar role.Strong hands-on experience with RDBMS technologies (Oracle, SQL Server, PostgreSQL, MySQL).Proven expertise in data masking, obfuscation, and anonymization techniques.Proficiency in SQL, PL/SQL, T-SQL, and database performance tuning.Experience with test data management tools (e.g., Delphix, Informatica TDM, IBM Optim, Broadcom TDM, or equivalent).Knowledge of data privacy regulations (GDPR, HIPAA, CCPA, PCI DSS).Strong scripting/programming skills (Python, Shell, or similar) for automation.Familiarity with CI/CD pipelines and DevOps workflows.Nice to HaveExperience with cloud databases (AWS RDS, Azure SQL, GCP Cloud SQL).Exposure to synthetic data generation frameworks.Knowledge of data virtualization technologies.Prior experience in the financial, healthcare, or telecom sector (where data privacy is critical).Soft SkillsStrong problem-solving and analytical mindset.Excellent communication and collaboration skills across engineering and QA teams.Ability to work independently in a fast paced environment.Attention to detail and a focus on data quality.EducationBachelors degree in Computer Science Information Technology or related field or equivalent experience