Python Data Analyst (BA + QA )

📍 Role Overview

We are seeking a Data Management Analyst with a strong blend of Business Analysis and Quality Assurance experience to support data management initiatives within the financial domain. The ideal candidate will have hands-on exposure to data warehouses, data quality, and reconciliation processes, and will work closely with business and technical stakeholders to ensure data accuracy, consistency, and reliability.

🎯 Key Responsibilities

• Act as a bridge between business users and technical teams to understand data requirements and translate them into functional specifications.
• Perform data validation, reconciliation, and quality checks, including implementation, monitoring, and issue resolution.
• Analyze data from data warehouses and source systems to identify gaps, inconsistencies, and improvement opportunities.
• Design and execute data quality test cases, support UAT, and ensure adherence to business rules.
• Manage SLA-driven support activities, including handling queries and issues raised by end users.
• Prepare and maintain functional and technical documentation such as BRDs, FRDs, data mapping documents, and SOPs.
• Collaborate with stakeholders to support data governance, controls, and continuous improvement initiatives.
• Participate in project discussions, requirement walkthroughs, defect triage, and data review sessions.

✅ Required Qualifications & Experience

• Bachelor’s degree in Computer Science, Information Technology, or related field.
• 3–7 years of experience in Data Management, preferably within the financial services industry.
• Strong experience in Data Warehouse environments (data validation, reporting layers, reconciliation).
• Proven background in Business Analysis and/or Data Quality/QA roles.
• Hands-on experience with data analysis and reconciliation activities.
• Working knowledge of SQL and Python for data analysis and validation (not heavy development).
• Experience handling end-user queries and SLA-based support.
• Strong experience in documentation (functional specs, data definitions, test scenarios, reports).
• Excellent problem-solving, communication, and stakeholder management skills.
• High attention to detail, data accuracy, and quality.
• Ability to manage multiple priorities in a fast-paced environment.

🌟 Nice to Have

• Experience with banking/financial data platforms.
• Exposure to data governance, metadata management, or regulatory reporting.
• Prior involvement in UAT or data migration/warehouse projects.