Job Description
• Perform data analysis to support business and operational requirements.
• Manage end-to-end data processing, including data extraction, transformation, validation, and reconciliation.
• Conduct data quality checks, identify discrepancies, and perform root-cause analysis and troubleshooting.
• Gather business and technical requirements and support implementation activities.
• Execute and support User Acceptance Testing (UAT) and production validation.
• Manage Service Level Agreements (SLA) and respond to data-related queries from end users in a timely manner.
• Monitor data pipelines and operational processes to ensure data accuracy and reliability.
• Prepare and maintain technical and functional documentation, including specifications and process guides.
• Collaborate with internal stakeholders to ensure smooth data operations and issue resolution.
Requirements
• Minimum 2 years of experience in data analysis or data operations support; candidates with 4–8 years of experience are preferred.
• Strong proficiency in SQL and Python for data querying, analysis, and automation.
• Hands-on experience with enterprise databases such as MS SQL, Snowflake, Redshift, and PostgreSQL.
• Experience with data integration tools, e.g. Informatica or equivalent ETL platforms.
• Proven experience in data reconciliation, data quality checks, and end-to-end data processing.
• Experience in performing and supporting UAT activities.
• Familiarity with finance domain data and financial reporting processes is an advantage.
• Strong problem-solving skills with logical and analytical thinking.
• Good communication skills and ability to manage user queries and operational support requests.
