Data Analyst (Data Transformation & Reconciliation)

About

Day to Day Job Duties

• Perform detailed data analysis to support large-scale transformation and migration initiatives.
• Analyze complex data structures across multiple source and target systems.
• Develop and maintain data mapping documents (source-to-target mappings).
• Write complex SQL queries for data validation, reconciliation, and impact analysis.
• Conduct system reconciliation between legacy and new platforms to ensure data integrity.
• Identify data gaps, inconsistencies, and quality issues and recommend remediation strategies.
• Partner with business stakeholders to gather data requirements and translate them into technical specifications.
• Support ETL validation, data migration testing, and production data verification.
• Create data dictionaries, metadata documentation, and business rule documentation.
• Develop dashboards and reports to communicate findings and transformation progress.
• Collaborate with engineering, QA, and business teams to resolve data-related issues.

Basic Qualifications

• Minimum 6+ years of experience in data analysis within enterprise environments.
• Minimum 4+ years of hands-on experience writing complex SQL queries.
• Strong experience in data mapping, data modeling concepts, and source-to-target documentation.
• Experience performing system reconciliation during large transformation or migration programs.
• Experience working with relational databases (Oracle, SQL Server, Snowflake, etc.).
• Experience supporting data migration, ETL, or cloud transformation initiatives.
• Strong analytical and problem-solving skills with attention to detail.
• Experience working in Agile or hybrid delivery environments.

Degree

Bachelor's degree in Computer Science, Information Systems, Business Analytics, or related field.

Nice to Have

• Experience with data visualization tools (Power BI, Tableau, OBIEE).
• Experience with big data platforms (Hadoop, Spark).
• Experience with cloud data platforms (AWS, Azure, Snowflake).
• Knowledge of data governance, data quality frameworks, and regulatory reporting.
• Experience in financial services, insurance, or other regulated industries.