Data Quality Analyst

In the context of the Data Quality Framework, the role of Data Quality Analyst in reference to the following scope of responsibility. Depending on the team, the associated tasks might be covered by R&D team members such as Data Engineers, Data Scientists and/or Developers:

• Data Profiling: Analyzes data sets to understand their structure, content, and quality. Identifies patterns, outliers, and anomalies.

• Quality Metrics: Develops and monitors key data quality metrics.

• Regular Audits: Conducts regular data quality audits to ensure data meets established standards and policies.

• Monitoring Tools: Utilizes data quality monitoring tools and techniques to continuously track data quality issues.

• Root Cause Analysis: Investigates data quality issues to determine their root causes and suggests corrective actions.

• Data Cleaning: Implements processes and tools to cleanse data, resolving issues related to duplicates, missing values, and inaccuracies.

• Best Practices: Promotes and enforces best practices for data quality management within teams.

• Cross-Functional Collaboration: Works closely with data engineers, data stewards, and other stakeholders to address data quality issues and implement improvements.

• Reporting: Prepares and presents reports on data quality findings, trends, and improvement initiatives to management and other stakeholders.

• Continuous Improvement: Identifies opportunities for improving data quality processes and implements initiatives to enhance data quality.

• Education: Provides training and support to data users and stakeholders on data quality standards and best practices.