Senior Analyst - Informatica Developer - Chennai - Immediate Joiners at WNSGlobalServices144

• At-least 5 yrs of Strong ETL Testing Experience using PythonPyspark • Analyse actuarial business requirements, source to target mappings, and transformation logic for actuarial data flows• Design and execute ETL test cases for actuarial datasets • Perform source to target reconciliation to validate actuarial metrics such as ultimate values, reserves, and loss ratios• Validate historical data movements, effective dated records, restatements, and development logic used in actuarial models• Conduct data quality checks to ensure completeness, accuracy, consistency. • Validate complex aggregation and transformation rules used in actuarial calculations.• Work closely with actuaries, data engineers, finance teams, and business analysts to investigate discrepancies and drive resolution• Log, track, and manage defects using defect tracking tools such as JIRA• Ensure compliance with audit, governance, and regulatory standards applicable to actuarial data________________________________________Required Skills & Experience• Strong experience in ETL testing within actuarial or insurance data environments• Strong Experience using Python for validation and automation.• Advanced SQL proficiency for complex reconciliations, aggregations, joins, and variance analysis• Hands-on experience with ETL tools (Informatica, DataStage, Talend, SSIS, or similar)• Solid understanding of actuarial data concepts, including: o Reserves and ultimate calculations• Strong knowledge of relational databases, data modeling, and dimensional schemas• Experience with test management and defect tracking tools• Strong analytical mindset with high attention to numerical accuracy and data integrity________________________________________Nice to Have• Exposure to modeling data flows• Experience testing data supporting actuarial• Understanding of actuarial systems or tools (e.g.,Prophet)• Scripting or automation experience for data validation and reconciliation• Experience working with large, long historical datasets• Experience in DataLake Concepts