Job Description

Responsible for identifying data quality issues, analyzing data sets, and working with various teams to improve data quality across the organization.

• Perform data profiling and analysis to assess the quality of data across different systems and sources.
• Identify and report data quality issues, including missing, duplicate, or inconsistent data, and recommend corrective actions.
• Monitor data quality KPIs (e.g., completeness, accuracy, timeliness, consistency) and track improvements over time.
• Implement data quality checks and validation rules to ensure that data meets the organization’s standards.
• Collaborate with data stewards, business analysts, and other teams to perform data cleansing activities, including data correction, enrichment, and de-duplication.
• Support the development and implementation of data standardization practices across the organization to ensure consistency in data entry and processing.
• Conduct root cause analysis of data quality issues and work closely with technical teams to identify and resolve the underlying problems.
• Track recurring data quality issues and develop long-term strategies to prevent them from reoccurring.
• Work with data governance and infrastructure teams to implement automated processes to improve data quality.
• Support data governance initiatives by helping define and enforce data quality standards, policies, and procedures. Document data quality processes and contribute to data governance documentation, including data dictionaries and metadata management.
• Collaborate with data engineering, data management, business intelligence, and IT teams to implement data quality best practices.
• Work with business units to understand their data needs and ensure data quality processes align with business objectives.
• Bachelor’s degree in data management, Information Systems, Computer Science, Statistics, or a related field.

Experience
• 2+ years of experience in data quality analysis, data management, or data governance.
• Experience with data profiling, cleansing, and validation tools (e.g., Informatica Data Quality, Talend, Microsoft Purview, Trillium).
• Strong proficiency in SQL for querying and analyzing large datasets.
Knowledge, Skills, Abilities, and Other Characteristics
• Strong understanding of data quality dimensions (accuracy, completeness, consistency, uniqueness, and timeliness).
• Experience with data profiling and analysis techniques to identify data anomalies and issues.
• Ability to perform data validation, root cause analysis, and data cleansing tasks.
• Proficiency in data visualization and reporting tools like Tableau, Power BI, or Excel.
• Strong analytical skills with the ability to problem-solve and make data-driven recommendations.
• Excellent attention to detail and ability to handle complex data sets.

Preferred Qualifications:
• Experience with data governance tools or data catalog systems (e.g., Collibra, Alation).
• Familiarity with cloud-based data platforms (e.g., AWS, Azure, Google Cloud).
• Knowledge of data privacy and compliance regulations (GDPR, CCPA) and how they impact data quality practices.