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.
