Senior Data Analyst - Payments

Role Overview

We are seeking a Senior Data Analyst with deep Payments domain experience and strong hands-on expertise in SQL and Python. This role will focus on analyzing large-scale transaction data, deriving business insights, and supporting decision-making across Payments platforms (ACH, Wire, Cards, RTP, etc.). The ideal candidate will combine strong technical skills with a solid understanding of Payments operations, compliance, and risk controls within a banking environment.

Key Responsibilities

• Analyze large volumes of Payments transaction data to identify trends, anomalies, and business insights
• Write complex, high-performance queries using advanced SQL (joins, CTEs, window functions, performance tuning)
• Develop data transformation and analytics scripts using Python (Pandas, Num Py, data wrangling)
• Create dashboards, reports, and performance metrics for business stakeholders
• Partner with Payments, Risk, Compliance, and Operations teams to support reporting and data-driven initiatives
• Perform data validation, reconciliation, and quality checks across Payments systems
• Support regulatory and operational reporting requirements
• Document business logic, data definitions, and analytics methodologies

Required Skills & Experience

• 10+ years of experience as a Data Analyst, with strong exposure to Payments Banking
• Deep understanding of Payments ecosystem (ACH, Wire, SWIFT, Cards, Clearing & Settlement, ISO 20022)
• Advanced proficiency in SQL (query optimization and large dataset handling)
• Strong programming skills in Python for data analysis and automation
• Experience working with data warehouses and large transactional databases
• Strong analytical thinking and problem-solving skills
• Excellent stakeholder communication and documentation skills

Preferred Qualifications

• Experience with BI tools (Tableau, Power BI)
• Exposure to fraud analytics, AML, or transaction monitoring systems
• Experience working in regulated banking environments
• Familiarity with Spark or distributed data processing frameworks