Data QA ( P&C domain

Responsibilities :Lead end-to-end data quality assurance initiatives to ensure accuracy, completeness, consistency, integrity, and reliability across data platforms. Collaborate with business, program, and engineering teams to identify data dependencies, assess risks, and provide architectural guidance for data transformation and modernization initiatives. Design and implement scalable testing strategies covering source-to-target validation, data reconciliation, transformation logic, aggregations, test data management, and business rule validation. Perform domain based testing, data profiling, anomaly detection, root-cause analysis, and support migration testing across legacy and modern cloud data platforms. Develop proof of concepts (POCs), resolve complex technical challenges, and drive continuous improvement through QA automation and industry best practices.

P&C domain experience a must. Bachelor s degree in engineering, Information Technology, Computer Science, or a related field. Strong experience in Data QA architecture for large-scale data modernization, migration, ETL/ELT, and data warehousing projects using cloud platforms such as Snowflake and Databricks. Deep expertise in data QA engineering, data governance, data lineage, data integration, data management, and validation of structured/hierarchical datasets such as JSON and XML. Excellent communication, visualization, and presentation skills with the ability to clearly explain complex technical concepts to both business and technical stakeholders.