Business Analyst
at Capgemini
Posted 6 days ago
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- Compensation
- Not specified
- City
- Not specified
- Country
- India
Currency: Not specified
Role: Business Analyst to support the development, refinement, and enhancement of investment banking data products and financial data assets. Gather, analyze, and document business requirements from stakeholders across Finance, Product Control, Middle Office, and Front Office; translate business and accounting rules into clear functional requirements for data pipelines, reporting, and analytics. Contribute to data dictionaries, data lineage, validation rules, and control frameworks. Leverage finance and accounting expertise to model P&L, balance sheet, and other financial metrics; perform data analysis using SQL, and prototype solutions with Python or VBA; collaborate with data engineering and cross-functional teams through UAT and go-live phases.
Job Description
Key Responsibilities
1. Business Analysis for Investment Banking Data Products
• Act as the primary BA supporting the development, refinement, and enhancement of investment banking data products and financial data assets.
• Gather, analyze, and document business requirements from stakeholders across Finance, Product Control, Middle Office, and Front Office functions.
• Translate business and accounting rules into clear functional requirements for data pipelines, reporting solutions, and analytical platforms.
• Support the creation of data dictionaries, data lineage documentation, validation rules, and control frameworks.
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2. Finance & Accounting Expertise
• Apply deep knowledge of accounting principles, financial statements, and product level accounting for investment banking products (e.g., derivatives, fixed income, equities, structured products).
• Support the design of data models for P&L, balance sheet, trade life cycle, valuations, and financial metrics.
• Partner with Finance stakeholders to ensure accurate representation of financial and accounting concepts within data platforms.
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3. Data Analysis & Technical Enablement
• Extract and analyze large datasets using advanced SQL to validate requirements, perform reconciliations, troubleshoot data quality issues, and identify process gaps.
• Use Python and/or VBA to build prototypes, automate recurring analyses, and assist with data validation frameworks.
• Collaborate with data engineering teams to ensure high quality data sourcing, transformations, and controls.
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4. Cross Functional Collaboration
• Work closely with Technology, Data Engineering, Finance, Risk, and Operations stakeholders to drive end to end project execution.
• Participate in solution design discussions, system testing (UAT), and go live support for new data features or product releases.
• Act as a subject matter expert (SME) on finance and accounting concepts during data product development cycles.
