Job Description

Role: Data Analyst Location: Nashville, TN (or) Alpharetta, GA Contract

Responsibilities

• Data Profiling: Analyze and examine large datasets to understand structure, completeness, accuracy, and relationships. Identify data anomalies, redundancies, and opportunities for standardization and improvement.
• Data Quality Assessment: Monitor, measure, and report on data quality metrics such as completeness, accuracy, consistency, timeliness, and uniqueness across key datasets and systems.
• Data Cataloging (EDO/Data Catalog): Maintain and curate the enterprise data catalog using tools such as Data EDO. Ensure that metadata, lineage, ownership, and business definitions are captured and updated.
• Data Quality Rule Creation: Design, implement, and maintain data quality rules and validation scripts. Collaborate with business and technical teams to translate requirements into effective data quality checks and alerts.
• Data Cleansing & Standardization: Develop and execute data cleansing and transformation routines to remediate quality issues and enforce enterprise standards.
• Stakeholder Collaboration: Work with data stewards, owners, data engineers, and business analysts to resolve data quality issues and enhance understanding of data assets.
• Documentation & Reporting: Prepare comprehensive data quality reports, visualizations, and dashboards to communicate findings and improvement initiatives to stakeholders.
• Continuous Improvement: Recommend and drive improvements in data quality processes, tools, and best practices.

Required Skills

• Good experience in data analysis, data quality, or data governance roles.
• Hands-on experience with data profiling, quality, and cataloging tools (e.g., Data EDO, Collibra, Informatica, Alation, Talend).
• Experience with data visualization/dashboarding tools (Tableau, Power BI, Looker).
• Experience in writing and deploying data quality rules, validations, and remediation scripts.
• Strong analytical, problem-solving, and documentation skills.
• Familiarity with modern data architectures (data lakes, warehouses) is an advantage.
• Advanced SQL skills and proficiency working with large structured and semi-structured datasets.
• Excellent written and verbal communication skills.

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