Data Analyst (Manhattan)

Title :- Data Analyst Location Manhattan, New York Work Model Hybrid – 3 days per week at NY office location Employment Type Contract or Full-time Role Overview The Data Analyst will analyze payment and enterprise data to support reporting, data quality, and business decision-making. The role will focus on SQL-based analysis, reconciliation, issue investigation, dashboard support, and data governance, with particular emphasis on CHIPS and wire-payment data. Key Responsibilities • Analyze payment and enterprise data to identify trends, discrepancies, and business insights. • Use SQL to query, validate, and reconcile data across multiple sources. • Investigate data-quality issues and work with business and technical teams to resolve them. • Define data requirements, measures, business rules, and reporting needs with stakeholders. • Build and validate dashboards, reports, and analytical outputs. • Support data governance through documentation of definitions, lineage, ownership, and quality rules. Ideal Candidate Profile • 9+ years of experience as a Data Analyst, or similar role working with complex datasets. • Strong SQL skills, including querying, validation, reconciliation, and root-cause analysis. • Experience with BI tools such as Power BI, Amazon QuickSight, or Tableau. • Working knowledge of data quality, lineage, metadata, ownership, and stewardship. • Strong analytical, communication, and stakeholder-management and problem solving skills. • Clear communication with technical and non-technical stakeholders. • Ownership of issues through root-cause analysis and resolution. • Strong attention to detail and consistency. • Ability to quickly build knowledge of CHIPS, wire payments, and related data. Required Qualifications • Experience with payments, banking, transaction, or financial-services data. • Experience with CHIPS, Fedwire, wire transfers, or ISO 20022 is strongly preferred. • Experience with AWS services such as S3, Athena, and QuickSight. • Experience with data-quality controls, reconciliation, and exception analysis. Education Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent experience. Pyramid Technology Solutions