Senior Data Analyst - Payments
Job Title: Senior Data Analyst – Payments
Location: Pittsburgh PA, Cleveland OH, Dallas TX
Experience: 10+ Years
Employment Type: Full-Time
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, NumPy, 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.
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