Senior Data Migration Analyst

Key Responsibilities Analyze complex source and target systems, schemas, data structures, and business rules. Develop and document end-to-end data migration strategies. Define source-to-target mappings and transformation requirements. Execute ETL processes from legacy environments to target platforms. Perform data profiling, cleansing, deduplication, validation, and reconciliation. Develop migration testing strategies and execute mock migration activities. Support migration cutover planning and execution. Investigate and resolve complex data quality and migration issues. Ensure accuracy, completeness, security, and integrity of migrated data. Collaborate with business stakeholders, technical teams, developers, DBAs, architects, and project managers. Develop migration runbooks and technical documentation. Prepare post-migration reconciliation and validation reports. Provide go-live and post-production migration support. Required Qualifications Bachelor's degree in Computer Science, Information Systems, Data Analytics , or related discipline. 11–15 years of relevant professional experience , preferably involving enterprise-scale data migration and data engineering projects. Advanced hands-on SQL skills with experience handling large datasets. Strong knowledge of ETL architecture, processes, and data transformation techniques . Strong proficiency in Python for ETL development, data analysis, validation, and transformation. Hands-on Databricks experience for cloud-based data engineering and migration. Strong PySpark skills for large-scale data processing and transformation. Experience working with relational databases such as SQL Server, Oracle, MySQL, or PostgreSQL . Strong understanding of data reconciliation, data quality, and data governance. Experience preparing migration strategies, mapping documents, test plans, and runbooks. Excellent analytical, problem-solving, communication, and stakeholder management skills. Preferred Qualifications Experience with one or more of the following is highly desirable: Informatica, Talend, SSIS, or Azure Data Factory Azure, AWS, or Google Cloud SAP, Oracle, Salesforce, or Workday migrations Enterprise data warehouse environments Reporting and analytics platforms Agile or hybrid delivery methodologies Data privacy, security, and regulatory requirements such as GDPR