Overview
Skills
Job Details
Title: Data Quality Analyst
Location: Remote
Client: State client
Minimum Qualifications
Minimum 5+ years of experience in data profiling, cleansing, analysis, and validation preferably within large-scale data migration or public sector systems.
Proven expertise with automated data quality tools and scripting (e.g., SQL, Python, data profiling utilities).
Demonstrated experience working with enterprise-level data warehouses or intermediate staging databases in data migration projects.
Summary
As a Data Quality Analyst, you will play a critical role in ensuring the accuracy, consistency, and integrity of data. You will lead efforts in data profiling, cleansing, validation, and quality monitoring using automated tools and scripting techniques. Working closely with project stakeholders, technical teams, and business users, you will help prepare and validate clean datasets for migration, establish quality standards, and support knowledge transfer for long-term data governance.
Job Description
Perform data profiling to identify anomalies, missing values, duplicates, and format inconsistencies across legacy and new systems (STAR and Gemini).
Design and configure automated tools to support profiling, cleansing, validation, and reconciliation processes.
Develop and execute SQL scripts to analyze, cleanse, and validate datasets stored across 1000+ database tables and multiple Excel-based sources.
Define data quality metrics and thresholds; continuously monitor data against these benchmarks.
Collaborate with stakeholders to define and document data cleansing and validation strategies.
Create and maintain data dictionaries, data mapping documents, and transformation logic.
Ensure compliance with data governance standards, business rules, and legal requirements.
Conduct data validation testing and sample verifications to confirm data accuracy and completeness.
Maintain a comprehensive audit trail for all data transformations, fixes, and validation results.
Assist in building intermediate SQL staging databases used for loading and migrating cleansed data.
Prepare data quality reports detailing issues identified, remediation actions taken, and items that remain unresolved.
Communicate clearly with project managers, developers, and business users to resolve data issues in a timely manner.
Participate in project planning sessions, helping estimate timelines and resources for data activities.
Support knowledge transfer and training to internal staff for continued data quality management post-project.
Participate in UAT (User Acceptance Testing) efforts, assisting in reconciliation of source-to-target data issues.
Document important processes for the client s team.