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# Data Engineer/DBA

- **Company:** Spectraforce
- **Location:** Charlotte, NC, United States
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Microsoft Excel, Extract Transform Load (ETL), Data Visualization, Data Warehousing, Relational Databases, Excel Formulas, Fraud Prevention and Detection, Microsoft SQL Server, Oracle (Applications), Pivot Tables, Power BI, SQL Databases, Tableau (Software), Data Processing, Macros, Snowflake, Vba Programming Language, Qlikview, Data Management
- **Published:** July 30, 2026
- **Apply:** http://leoforce.us/Careers/Spectraforce/JobDetails.html?jobid=bc3ac5b2-856b-4c5e-b230-bce599c8c584&OrgId=1&UserId=2285

## About the Role

* 5 years of experience as a Data Analyst, preferably within banking, financial services, or a regulated industry.
 * Proficiency in SQL for querying and manipulating data from relational databases.
 * Hands-on experience with data visualization tools such as Tableau, Power BI, or Qlik.
 * Working knowledge of Excel (advanced formulas, pivot tables, macros/VBA a plus).
 * Understanding of core banking data domains: deposits, loans, payments, credit risk, or fraud detection.

## Description

* Gather, clean, validate, and analyze large financial datasets from core banking systems, data warehouses, and third-party sources.
 * Design and maintain dashboards and reports (e.g., in Tableau, Power BI, or similar) to track KPIs such as loan performance, deposit trends, credit risk, fraud indicators, and profitability.
 * Write and optimize SQL queries to extract and transform data from relational databases and data warehouses (e.g., Snowflake, Oracle, SQL Server).
 * Partner with Risk, Compliance, Finance, and Operations teams to support regulatory reporting (e.g., CCAR, BSA/AML, Basel III) and internal audits.
 * Perform statistical analysis and build models to identify trends, anomalies, and opportunities in customer behavior, credit risk, and operational efficiency.
 * Ensure data quality, consistency, and governance in accordance with the bank's data management policies and regulatory requirements.
 * Translate business requirements into analytical solutions and present findings to stakeholders and senior leadership in a clear, actionable format.
 * Support process automation and reporting efficiency initiatives, including ETL pipeline support and documentation.
 * Maintain documentation of data definitions, business rules, and analytical methodologies for audit and governance purposes.


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