Data Quality Analyst

Avalore, LLC•Arlington, VA

13h•$85,000 - $184,000•Onsite

About The Position

The Data Quality Analyst will monitor and ensure data integrity and accuracy across the Advana platform. This person will implement data quality tools and processes, define quality metrics, investigate and resolve anomalies, and work with data stewards to enforce standards. This person will develop and implement data quality assessment frameworks, create and maintain data quality rules and validation checks, and perform regular data quality audits. This person will analyze data quality issues and their root causes, coordinate with data owners to resolve quality problems, and track data quality metrics over time. This person will establish data quality monitoring and alerting, develop data cleansing and enrichment procedures, and create reports on data quality status for stakeholders. This person will participate in data governance activities related to quality, provide guidance on data quality best practices, and collaborate with data engineers to implement quality controls in data pipelines. This person will develop and maintain data quality documentation, train users on data quality principles and practices, and evaluate data quality tools for potential adoption.

Requirements

SECRET Security Clearance Required
GSEC, SSCP, or Security+ certification (for Junior/Journeyman roles)
CCISO, CISM, CISSP, or GSLC certification (for Senior roles)
Bachelor's Degree
Good communication skills
Self-starter mindset
Professional proficiency in English is required.
Demonstrated proficiency in using all Microsoft Office applications.
Currently authorized to work in the United States on a full-time basis.

Responsibilities

Monitor and ensure data integrity and accuracy across the Advana platform.
Implement data quality tools and processes.
Define quality metrics.
Investigate and resolve anomalies.
Work with data stewards to enforce standards.
Develop and implement data quality assessment frameworks.
Create and maintain data quality rules and validation checks.
Perform regular data quality audits.
Analyze data quality issues and their root causes.
Coordinate with data owners to resolve quality problems.
Track data quality metrics over time.
Establish data quality monitoring and alerting.
Develop data cleansing and enrichment procedures.
Create reports on data quality status for stakeholders.
Participate in data governance activities related to quality.
Provide guidance on data quality best practices.
Collaborate with data engineers to implement quality controls in data pipelines.
Develop and maintain data quality documentation.
Train users on data quality principles and practices.
Evaluate data quality tools for potential adoption.