Data Analyst at UBCI

Location: Atlanta, Georgia
Posted: May 14, 2026

Description

The Data Analyst will transform organizational data into actionable insights to support decision-making, performance management, and regulatory compliance. This role involves analyzing various data sets, creating visualizations like Power BI and Tableau, developing KPIs, and contributing to data governance initiatives.

Required Skills

Data Analysis
KPI Development
Dashboard Creation
Automated Reporting
Data Quality

Additional Information

Preferred Qualifications: Ability to identify, collect, and analyze relevant data aligned with business needs.
Experience producing descriptive, exploratory, and diagnostic analyses to understand trends, behaviors, and anomalies.
Proficiency in designing and maintaining analytical datasets such as data marts and analytical views.
Skill in developing KPIs, ratios, and ad hoc analyses to achieve business and regulatory goals.
Expertise in creating interactive and dynamic dashboards using Power BI, Tableau, or Qlik.
Ability to set up automated reporting systems for performance management, regulatory, and periodic purposes.
Strong documentation skills for defining KPIs, calculating rules, specifying scope, and detailing sources.
Understanding of banking processes and associated data-related challenges, particularly credit risk, AML/CFT, compliance, and financial performance.
Ability to interpret, challenge, and rephrase business needs into clear analytical issues.
Capacity to translate business problems into data-driven analyses and generate actionable recommendations.
Effective communication skills to present analysis results clearly, structurally, and educatively.
Involvement in Data and Governance committees to advocate for analytical aspects.
Contributing to the identification of new analytical use cases that offer significant value.
Application of quality, harmonization, and standardization rules established by the CDO/DMO.
Identification of inconsistencies, breakpoints, duplicates, or anomalies within analyzed data.
Escalating data quality incidents to appropriate teams such as Data Stewards, Data Quality Operations, and Data Engineers.
Active contribution to the data catalog, encompassing business metadata and KPI definitions.
Production of anomaly reports along with proposed improvement actions.
Adherence to security, confidentiality, and compliance regulations regarding data usage.