Senior Consultant-Data Analyst

Responsibilities:

• Perform data profiling on source and target systems to assess data completeness, accuracy, and consistency.
• Execute data remediation activities to resolve data anomalies and ensure compliance with KYC and CLM standards.
• Implement data quality checks and document findings to support governance and audit requirements.
• Prepare and maintain detailed data profiling and remediation documentation aligned with project timelines.
• Design, prepare, and execute test cases for data migration validation.
• Create and manage test data (synthetic or masked production data) for SIT and UAT cycles.
• Perform SIT validation to ensure end-to-end data integrity, accuracy, and regulatory compliance.
• Collaborate with QA teams to log defects, track resolutions, and verify fixes.
• Develop, validate, and maintain Power BI dashboards to monitor data migration progress, data quality metrics, and SIT results.
• Ensure dashboards provide clear, actionable insights for project stakeholders.
• Work closely with business analysts, data architects, and developers to validate data mappings and transformations.
• Participate in remediation discussions and provide data-driven recommendations.

Requirements:

• Bachelor's degree in any field
• Minimum 10 years of experience in data analysis roles, preferably supporting data migration initiatives.
• Strong experience in banking or financial services projects.
• Proven expertise in data profiling, data quality assessment, and data remediation.
• Proficiency in SQL for data validation, reconciliation, and analysis.
• Hands-on experience with Power BI for dashboard development and reporting.
• Knowledge of test case design, test data preparation, and SIT validation processes.
• Familiarity with data migration methodologies and KYC / CLM regulatory requirements.
• Strong documentation, communication, and collaboration skills.
• Experience with ETL tools such as Informatica, Talend, or SSIS is a plus.
• Exposure to data modeling, metadata management, or automation scripting for data validation is advantageous.