What are the responsibilities and job description for the Senior Data Analyst Lead position at TUPPL Technology Inc?
Job Title: Senior Data Analyst Lead
Location: Pittsburgh, Cleveland, Dallas
Employment Type: Full-Time
Role Overview
We are seeking a Senior Data Analyst Lead with deep Banking 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.
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 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
• 8-10 years of experience as a Data Analyst, with strong exposure to Banking.
• 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.