Data Quality Analyst - Secret-Cleared & Data Governance

Avalore, LLC; Virginia (MN); On-site; USD 85,000 - 184,000; Full time

Benefits offered by this job

Health care plan

401k/IRA

Life insurance

Paid time off

Disability

Training & development

Employee assistance program

Job summary

Avalore, LLC is seeking a Data Quality Analyst to monitor and improve data integrity across the Advana platform. You will implement data quality tools, define metrics, investigate anomalies, and work with data stewards to enforce standards.

Responsibilities include developing data quality frameworks, maintaining validation checks, auditing quality, and collaborating with data engineers to embed quality controls in pipelines.

Qualifications

• Security clearance required based on role level.
• GSEC, SSCP, or Security+ certification for Junior/Journeyman.
• CCISO, CISM, CISSP, or GSLC certification for Senior.
• Three role levels: Junior, Journeyman, Senior with education requirements.
• Must have good communication and a self-starter mindset.
• Proficient in English.
• Proficiency with Microsoft Office applications.
• Authorized to work in the United States without visa sponsorship.

Responsibilities

• Monitor and ensure data integrity across the Advana platform.
• Define data quality metrics, investigate anomalies, and resolve issues.
• Develop data quality frameworks, rules, and validation checks.
• Coordinate with data owners and data stewards on standards.
• Participate in data governance activities and report status to stakeholders.

Skills

Good communication

Self-starter mindset

English proficiency

Microsoft Office proficiency

Education

Bachelor's Degree

Tools

Microsoft Office

Job description

Avalore, LLC is seeking a Data Quality Analyst to monitor and improve data integrity across the Advana platform. You will implement data quality tools, define metrics, investigate anomalies, and work with data stewards to enforce standards.

Responsibilities include developing data quality frameworks, maintaining validation checks, auditing quality, and collaborating with data engineers to embed quality controls in pipelines.