Technical Data Analyst

*Responsibilities:**Data Analysis & Data Profiling*·      Perform detailed analysis and profiling ofsource and target system data to assess data quality, identify inconsistencies,and mitigate migration risks.·      Analyze customer, KYC, onboarding, and referencedata to identify data quality issues, anomalies, and business impacts.·      Conduct data discovery and assessment exercisesto understand data structures, relationships, and dependencies.·      Define and monitor data quality metrics,baseline assessments, and governance controls throughout the migrationlifecycle.*Data Mapping & Migration Design*·      Develop comprehensive source-to-target datamapping specifications.·      Translate business requirements into detailedfunctional and technical specifications.·      Define migration rules, transformation logic,enrichment requirements, validation criteria, and reconciliation processes.·      Collaborate with business stakeholders toresolve data ambiguities, mapping gaps, and data-related issues.*Data Quality & Anomaly Detection*·      Analyze data to identify anomalies, duplicates,missing records, and data inconsistencies.·      Investigate root causes of data quality issuesand recommend remediation strategies.·      Define and execute data quality controls toensure data integrity throughout the migration lifecycle.·      Support data cleansing, enrichment, andremediation initiatives.*ETL & Migration Pipeline Validation*·      Partner with ETL developers and technical teamsto validate migration pipelines and data transformation processes.·      Review ETL designs, transformation logic, anddata processing workflows to ensure alignment with business rules.·      Troubleshoot migration failures, exceptions,reconciliation discrepancies, and performance issues.·      Validate data transformations and migrationoutcomes against agreed business requirements.*Testing & Reconciliation*·      Design and execute migration testing activities,including User Acceptance Testing (UAT), mock migrations, dry runs, andproduction validation.·      Perform detailed source-to-target reconciliationto ensure data completeness, accuracy, and consistency.·      Validate record counts, data integrity,transformation results, and migration success criteria.·      Support defect tracking, issue resolution, andtest result reporting.*Requirements:*·      Proven experience working within Banking orFinancial Services environments.·      Strong understanding of KYC/eKYC processes,customer onboarding, Customer Due Diligence (CDD), and regulatory compliancedata requirements.·      Experience delivering large-scale datamigration, transformation, or modernization programs.·      Strong hands-on experience with Microsoft SQLServer.·      Advanced SQL development and querying skills,including complex joins, stored procedures, functions, views, Common TableExpressions (CTEs), performance optimization, and data validation queries.·      Strong understanding of relational databases,data modelling, data warehousing concepts, and data migration methodologies.·      Experience working with ETL pipelines, dataintegration processes, and data transformation workflows.·      Demonstrated expertise in data profiling, datamapping, data reconciliation, data quality assessment, and root cause analysis.·      Ability to analyze, interpret, and validatelarge and complex datasets.·      Experience with source-to-target mapping,migration rule definition, and data validation activities.·      Strong analytical, troubleshooting, andproblem-solving skills with the ability to identify data anomalies and driveresolution.·      Experience in banking data transformation,migration, or regulatory data programs is highly preferred.·      Knowledge of data governance principles and dataquality frameworks is advantageous.·      Experience with data migration tools,frameworks, and automation solutions is preferred.·      Knowledge of Power BI or other reporting andanalytics platforms is an added advantage.·      Experience working in multinational or regionalbanking environments is preferred.