Data Analyst - Financial Services

Role Overview

We are looking for an experienced Senior Data Analyst with strong expertise in SQL, data analysis, and the Financial Services domain. The role involves analyzing complex financial data, performing data validation, reconciliation, root cause analysis, and supporting business and technology teams with data-driven solutions.

Key Responsibilities

• Analyze large volumes of financial services data across banking, lending, payments, cards, insurance, risk, compliance, and financial operations.
• Develop complex SQL queries for data extraction, transformation, validation, and analysis.
• Perform data profiling, data quality checks, reconciliation, and issue investigation.
• Analyze customer, account, transaction, product, financial, and operational data.
• Work with business and technology teams to understand requirements and translate them into data solutions.
• Perform source-to-target data mapping, impact analysis, and support data migration activities.
• Identify data discrepancies, perform root cause analysis, and drive resolution.
• Analyze data trends and identify patterns, exceptions, and business insights.
• Create analytical reports, dashboards, and management insights.
• Support data testing, UAT, implementation, and production activities.
• Work with stakeholders to define data requirements, business rules, validation logic, and reporting requirements.

Required Skills & Experience

• 610 years of experience as a Data Analyst in Financial Services / Banking / BFSI.
• Strong hands-on expertise in SQL, including complex joins, subqueries, CTEs, window functions, and query optimization.
• Strong experience with relational databases such as Oracle, PostgreSQL, SQL Server, or similar.
• Good understanding of one or more below Financial Services concepts such as:
• Banking and lending
• Payments and cards
• Customer and account data
• Financial transactions
• Risk and compliance
• Reconciliation and financial operations
• Insurance or wealth management
• Experience working with large datasets, data investigation, and data quality frameworks.
• Experience with ETL concepts, data flows, data transformation, and source-to-target mapping.
• Experience in data reconciliation, validation, and root cause analysis.
• Ability to work independently with business stakeholders, product teams, technology teams, and data engineering teams.