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Analyze, review, and maintain insurance and broker databases to ensure data accuracy, completeness, consistency, and usability. Perform data clean-up and data quality activities, including identifying duplicates, inconsistencies, missing information, and data integrity issues. Support data migration initiatives, including data extraction, validation, transformation, reconciliation, and post-migration data verification. Develop and maintain data mapping between source and target systems, ensuring business and technical requirements are accurately translated. Conduct detailed data review and analysis to identify trends, discrepancies, gaps, and opportunities for process or data improvement. Work closely with business and technical stakeholders to understand data requirements, business rules, and data structures. Analyze insurance-related data and databases, with an understanding of insurance, brokerage, or accounting processes preferred. Support the organization’s transition toward becoming an AI-ready organization by improving data quality, consistency, accessibility, and readiness for analytics and AI initiatives. Assist in establishing and maintaining data standards, validation rules, documentation, and data governance practices. Prepare data analysis reports, documentation, and findings for business and technical stakeholders. Collaborate with Data Engineers, Business Analysts, IT teams, and business users to resolve data-related issues and ensure successful delivery of data initiatives. Participate in testing and validation activities to ensure migrated, mapped, and transformed data meets defined business requirements. Qualifications: Bachelor’s degree in Computer Science, Information Technology, Data Analytics, Business, Accounting, or a related field. 5+yrs of experience in Data Analysis, Data Cleansing, Data Migration, and Data Mapping. Experience working with insurance, brokerage, financial services, or accounting data is highly preferred. Strong analytical and problem-solving skills with excellent attention to detail. Experience working with databases and structured datasets; SQL knowledge is an advantage. Good understanding of data quality, data governance, and data validation principles. Strong communication and stakeholder management skills. Ability to work effectively with both business and technical teams. Interest or experience in AI/data-readiness initiatives is a plus.