Data Quality Analyst

Booz Allen Hamilton•Warner Robins, GA

2d•Onsite

About The Position

The Data Quality Analyst position will support the collection, organization, validation, and preparation of asset information used in reporting and data visualization products. This position will work with team members to identify data-quality issues, maintain consistent standards, document corrections, and prepare accurate datasets for downstream use. The ideal candidate is detail-oriented, organized, comfortable working with large datasets, and willing to learn new tools and processes in an evolving technical environment.

Requirements

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
Ability to document work and communicate data-related questions clearly
Ability to work independently and collaborate within a small team
Ability to learn new software, tools, and technical processes
Top Secret clearance
Bachelor’s degree

Nice To Haves

Experience with data-transformation tools such as Power Query
Experience with reporting and visualization platforms such as Qlik Sense, Power BI, or Tableau
Experience with SQL, databases, or cloud-based data platforms
Experience with IT asset management, inventory, logistics, or configuration-management data
Experience with collaborative file-management platforms such as SharePoint
Experience with data governance, data dictionaries, or reference-data management
Experience working in a government, defense, or regulated environment
Ability to develop or improve standard operating procedures
Possession of strong attention to detail and organizational skills

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.
Compare information across source documents, reference lists, and working datasets.
Document data corrections, exceptions, and unresolved issues.
Prepare validated datasets for reporting, publication, and dashboard use.
Coordinate with data collectors, reviewers, and technical team members to resolve data issues.
Maintain organized records and support repeatable data-management processes.
Assist with improving data-entry, validation, and reporting procedures.
Learn and use new data-management and visualization tools as required.
Exercise sound judgment and avoid making unsupported assumptions about data.
Recognize and communicate uncertainty or exceptions requiring additional review.
Balance accuracy and attention to detail with operational timelines.
Demonstrate accountability, adaptability, and a process-improvement mindset.