Financial Business Intelligence Analyst

As a Financial Business Intelligence Analyst, will leverage data analytics, financial modeling, and business intelligence tools to transform complex financial data into actionable insights. You will work cross-functionally with finance and IT teams to design dashboards, build ETL pipelines, and deliver intelligence reports that drive strategic decision-making for clients and internal stakeholders., * Analyze large financial datasets to identify trends, patterns, and anomalies in revenue, cost, and investment performance using Python (Pandas, NumPy) and SQL

• Design and develop interactive financial dashboards and reports using Power BI and Tableau for client decision-making and KPI tracking
• Build and maintain ETL pipelines using SQL Server Integration Services (SSIS) to consolidate financial data from multiple source systems into centralized data warehouses
• Perform variance analysis comparing actual vs. budgeted financial performance and present findings to client stakeholders
• Develop quantitative models for portfolio performance analysis, asset allocation, and risk assessment applying Modern Portfolio Theory and statistical methods
• Conduct scenario analysis and stress testing on financial models to evaluate investment strategies and risk exposure
• Calculate and monitor risk metrics including Value at Risk (VaR), Sharpe Ratio, and drawdown analysis for client portfolios
• Utilize Bloomberg Terminal data to support financial market analysis, equity research, and investment reporting
• Write and optimize complex SQL queries, stored procedures, and views to support financial reporting environments
• Translate business requirements from finance teams into technical BI specifications and deliver actionable financial intelligence reports
• Document data definitions, business rules, and financial reporting standards for internal and client use
• Collaborate with IT and finance teams to ensure data integrity and accuracy across SQL Server databases supporting financial reporting

• 3+ years' experience in a financial analytics, business intelligence, or data analyst role - experience in financial services or investment management is ideal

• Proven track record of delivering end-to-end BI solutions, from gathering business requirements through deployment and stakeholder presentation

• Strong understanding of financial concepts including P&L analysis, budgeting and forecasting, portfolio analytics, and risk management

• Hands-on experience with ETL development and data warehouse architecture

• Demonstrated ability to translate complex financial data into clear, visually compelling dashboards and reports

• Experience working with large-scale relational databases and writing advanced SQL

• Familiarity with Agile/Scrum development environments

• Excellent analytical, communication, and organizational skills with the ability to present to both technical and non-technical audiences

• Positive, solution-focused attitude with the ability to manage multiple priorities

• Ability to influence key stakeholders on data-driven decisions

• Customer or client-facing experience is a strong plus Essential and Desirable Skills

• Proficiency in Power BI (DAX, Power Query, data modeling) and Tableau for interactive dashboard development

• Advanced SQL skills including stored procedures, CTEs, window functions, and query optimization on SQL Server

• Experience with Python for data analysis (Pandas, NumPy, Matplotlib/Seaborn) and automation

• Hands-on experience with SSIS for ETL pipeline development and data integration

• Working knowledge of Bloomberg Terminal for financial data retrieval and market analysis

• Knowledge of statistical methods and quantitative finance concepts (VaR, Sharpe Ratio, Monte Carlo simulation) is a strong plus

• Familiarity with Excel-based financial modeling including VBA/macros

• Experience with version control systems (Git) and CI/CD practices for BI deployments

• Knowledge of cloud-based data platforms (Azure SQL, Azure Data Factory, AWS Redshift) is a plus

• Working knowledge of Jira and Confluence for project tracking and documentation

• Exposure to R, SAS, or MATLAB for advanced statistical analysis is desirable Educational Requirements Bachelor's or Master's degree in Finance, Economics, Data Science, Statistics, Computer Science, Information Systems, or a related quantitative field.