Data Migration Analyst

Supports the Data Migration Lead by executing day-to-day data migration governance, validation, and reporting activities. Acts as the internal analyst counterpart to the vendor migration team and helps ensure the accuracy, completeness, and auditability of migration outputs.

Responsibilities

• Maintain and update migration workplan trackers, including mock run schedules, data refresh plans, reconciliation checkpoints, and cutover readiness checklists.
• Support requirements-to-data traceability through mapping trackers and transformation rule documentation.
• Perform data validation activities using agreed control frameworks, including record counts, control totals, sample checks, and exception analysis.
• Support reconciliation activities, including balance reconciliations, account-level variance reviews, and GL/SL tie-outs where applicable.
• Manage defect and exception logs, including root cause tracking and closure monitoring.
• Coordinate data-related SIT and UAT readiness activities, including data refresh, masking, and issue resolution.
• Prepare governance and audit documentation such as mapping approvals, reconciliation reports, sign-off packs, and runbooks.
• Produce status reports and dashboards covering progress, risks, issues, and milestones.
• Support cutover activities and mock runs, including reporting and post-run analysis.
• Ensure compliance with data security and access control standards.

• 5–8 years of experience in data analysis, system implementation support, testing support, PMO, or business analysis roles with strong data exposure.
• Experience in banking or financial services is preferred.
• Experience supporting data migration, reconciliation, or test data activities is an advantage.
• Familiarity with core banking and deposits concepts such as CASA and Time Deposit is a plus.
• Experience with legacy-to-modern platform migrations is strongly preferred.
• Hands-on experience with TCS, Finacle, or Fiserv platforms, with experience in at least two of these platforms.
• Knowledge of data quality and validation concepts.
• Understanding of ETL concepts and the data migration lifecycle.
• Understanding of banking data objects, including customer and account data, balances, product parameters, and transaction history.
• Strong analytical skills with the ability to work with large datasets and identify patterns, discrepancies, and variances.
• Proficiency in SQL and Excel; experience with Power BI or similar tools is an advantage.
• Strong documentation skills with attention to detail.
• Good communication and stakeholder coordination skills.
• Strong problem-solving and issue analysis capabilities.