Join the Fraud/AML Squad as a Senior Data Analyst within Enterprise Data & Information Services (EDIS). In this role, you’ll help build and enhance enterprise data pipelines that power reporting, analytics, and business insights across the organization. You will own data mapping for multiple data assets and play a key role in ensuring high‑quality, trusted data delivery to downstream consumers.
This is a hands‑on, highly collaborative role ideal for someone who thrives in complex data environments, understands financial‑services risk domains, and enjoys mentoring others.
Own attribution mapping for data elements from source systems to Fraud, AML, and other downstream marts within the Data Supply Chain (DSC)
Translate business requirements into detailed mapping documents; develop and unit‑test datasets using maintainable, reusable code
Conduct peer code reviews and contribute to continuous improvement initiatives
Mentor and train junior business and data analysts
Evaluate new and emerging data solutions, providing design guidance and technical recommendations
Contribute to technical documentation, specifications, and project artifacts
Ensure adherence to data standards and help extend best practices across the Fraud/AML squad
Provide input into data models and ERDs; use these artifacts to write efficient SQL
Create and enhance context diagrams to support auditability
Define business rules, transformation logic, derived expressions, SQL, and other components required for mapping documentation
Participate in Mapping Review Sessions and Data Architecture Review Sessions
Support portfolio planning, prioritization, and remediation activities
Apply strong knowledge of risk management practices within financial institutions or financial data environments
Education:
Master’s degree + 5+ years data analytics experience
OR Bachelor’s degree + 8+ years data analytics experience
OR equivalent military/work experience
3+ years of hands‑on SQL experience
Experience with Google Cloud Platform (GCP), especially BigQuery
Strong background in analyzing and interpreting business data, including automated data quality validation techniques
Excellent written and verbal communication skills
Experience with Agile methodologies, Jira, and Confluence
High attention to detail and strong organizational skills
Ability to manage multiple priorities in a fast‑paced environment
Experience in AML, Fraud, or Financial Services (preferred)
Experience with Ab Initio or other ETL tools (preferred)
Hybrid schedule; candidates must live within a 35‑mile radius of one of the following:
Cleveland, OH
Columbus, OH
Albany, NY
Buffalo, NY