Technical Data Analyst 

Job Description

Responsibilities:

Data Analysis & Data Profiling

• Perform detailed analysis and profiling of source and target system data to assess data quality, identify inconsistencies, and mitigate migration risks.
• Analyze customer, KYC, onboarding, and reference data to identify data quality issues, anomalies, and business impacts.
• Conduct data discovery and assessment exercises to understand data structures, relationships, and dependencies.
• Define and monitor data quality metrics, baseline assessments, and governance controls throughout the migration lifecycle.

Data Mapping & Migration Design

• Develop comprehensive source-to-target data mapping specifications.
• Translate business requirements into detailed functional and technical specifications.
• Define migration rules, transformation logic, enrichment requirements, validation criteria, and reconciliation processes.
• Collaborate with business stakeholders to resolve data ambiguities, mapping gaps, and data-related issues.

Technical & Functional Documentation

• Create and maintain Functional Specifications, Technical Documents, Data Mapping Documents, Validation & Reconciliation Reports, Test Plans, and Test Cases.
• Ensure all documentation complies with project governance, regulatory, and audit requirements.
• Maintain accurate and up-to-date project artifacts to support migration execution and knowledge transfer.

Data Quality & Anomaly Detection

• Analyze data to identify anomalies, duplicates, missing records, and data inconsistencies.
• Investigate root causes of data quality issues and recommend remediation strategies.
• Define and execute data quality controls to ensure data integrity throughout the migration lifecycle.
• Support data cleansing, enrichment, and remediation initiatives.

ETL & Migration Pipeline Validation

• Partner with ETL developers and technical teams to validate migration pipelines and data transformation processes.
• Review ETL designs, transformation logic, and data processing workflows to ensure alignment with business rules.
• Troubleshoot migration failures, exceptions, reconciliation discrepancies, and performance issues.
• Validate data transformations and migration outcomes against agreed business requirements.

Testing & Reconciliation

• Design and execute migration testing activities, including User Acceptance Testing (UAT), mock migrations, dry runs, and production validation.
• Perform detailed source-to-target reconciliation to ensure data completeness, accuracy, and consistency.
• Validate record counts, data integrity, transformation results, and migration success criteria.
• Support defect tracking, issue resolution, and test result reporting.

Stakeholder Management

• Collaborate with Business Users, Compliance, Operations, Data Governance, and Technology teams to gather requirements and address data challenges.
• Facilitate workshops and stakeholder discussions to clarify requirements, resolve issues, and drive decision-making.
• Communicate analysis findings, project risks, recommendations, and status updates to project stakeholders.
• Support project governance activities, status reporting, and issue management to ensure successful project delivery.

Requirements:

• Bachelor’s Degree in Computer Science, Information Technology, Data Analytics, Engineering, or a related discipline.
• Minimum 10 years of experience in Data Analysis, Data Migration, Data Management, or related disciplines.
• Proven experience working within Banking or Financial Services environments.
• Strong understanding of KYC/eKYC processes, customer onboarding, Customer Due Diligence (CDD), and regulatory compliance data requirements.
• Experience delivering large-scale data migration, transformation, or modernization programs.
• Strong hands-on experience with Microsoft SQL Server.
• Advanced SQL development and querying skills, including complex joins, stored procedures, functions, views, Common Table Expressions (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, data integration processes, and data transformation workflows.
• Demonstrated expertise in data profiling, data mapping, data reconciliation, data quality assessment, and root cause analysis.
• Ability to analyze, interpret, and validate large and complex datasets.
• Experience with source-to-target mapping, migration rule definition, and data validation activities.
• Strong analytical, troubleshooting, and problem-solving skills with the ability to identify data anomalies and drive resolution.
• Excellent communication and stakeholder management skills, with the ability to collaborate effectively across business and technology teams.
• Strong attention to detail and commitment to maintaining high data quality standards.
• Ability to work independently and manage multiple priorities in a fast-paced project environment.
• Experience in banking data transformation, migration, or regulatory data programs is highly preferred.
• Knowledge of data governance principles and data quality frameworks is advantageous.
• Experience with data migration tools, frameworks, and automation solutions is preferred.
• Knowledge of Power BI or other reporting and analytics platforms is an added advantage.
• Experience working in multinational or regional banking environments is preferred.

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