Remote Data Quality Analyst: Asset Data Validation

Bah; Warner Robins (GA); On-site; USD 78,000 - 176,000; Full time

Job summary

Booz Allen is seeking a Data Quality Analyst to support collection, organization, validation, and preparation of asset information for reporting and data visualization. You will work with team members to fix data-quality issues, document corrections, and prepare datasets for downstream use.

The role requires strong attention to detail, experience with large datasets, and a willingness to learn new tools and processes in a dynamic environment.

Qualifications

• 3+ years of experience with data analysis and validation, data management, or quality assurance.
• Experience using Microsoft Excel to enter, organize, review, or analyze data.
• Experience working with datasets such as structured records, spreadsheets, or inventories.
• Ability to identify missing, duplicate, or inconsistent information.
• Ability to follow documented procedures, naming standards, and quality-control requirements.

Responsibilities

• Enter, review, organize, and maintain asset-related data.
• Review datasets for missing, duplicate, inconsistent, or potentially inaccurate information.
• Apply established naming conventions, validation rules, and data-quality standards.
• Prepare validated datasets for reporting, publication, and dashboard use.
• Coordinate with data collectors, reviewers, and technical team members to resolve data issues.
• Assist with improving data-entry, validation, and reporting procedures.

Skills

Data analysis

Excel

Data validation

Documentation

Teamwork

Learning

Security clearance

Education

Bachelor's degree

Tools

Power Query

Qlik Sense

Power BI

Tableau

SQL

SharePoint

Job description

Booz Allen is seeking a Data Quality Analyst to support collection, organization, validation, and preparation of asset information for reporting and data visualization. You will work with team members to fix data-quality issues, document corrections, and prepare datasets for downstream use.

The role requires strong attention to detail, experience with large datasets, and a willingness to learn new tools and processes in a dynamic environment.