Data Governance - Data Quality Analyst

Job Description:

Responsible for ensuring the accuracy, completeness, and reliability of data within an organization. Their primary role is to assess, monitor, and improve the quality of data to support effective decision-making and business operations. A Data Governance - Data Quality Analyst plays a vital role in maintaining the integrity and reliability of data within an organization, enabling better decision-making, improved operational efficiency, and compliance with data governance standards.

The key responsibilities of a Data Governance Analyst – Data Quality typically include:

• Data profiling and analysis:
• Conducting in-depth analysis of data to identify inconsistencies, errors, and anomalies, and assessing data quality against defined standards and requirements.
• Data cleansing and validation:
• Developing and implementing data cleansing processes to correct errors, remove duplicates, and standardize data formats. Validating data accuracy and integrity through various techniques such as data matching and data validation rules.
• Data quality monitoring:
• Establishing data quality metrics and monitoring systems to continuously assess data quality levels. Identifying trends, patterns, and issues related to data quality and proactively addressing them.
• Data governance and compliance:
• Collaborating with data governance and data stewards teams to ensure adherence to data quality standards, policies, and regulatory requirements. Participating in data governance initiatives and providing input on data quality-related matters.
• Data documentation and reporting:
• Creating and maintaining documentation related to data quality processes, standards, and procedures. Generating reports and presenting findings on data quality metrics, issues, and improvement initiatives to stakeholders.
• Data quality improvement:
• Developing plans to improve data quality, including data cleansing, data enrichment, and data standardization efforts. Collaborating with relevant teams to address root causes of data quality issues.
• Data quality training and awareness:
• Conducting training sessions and workshops to educate users and stakeholders on data quality best practices, data entry guidelines, and data quality management techniques.
• Data integration and migration:
• Assisting in data integration and migration projects by ensuring data quality during the process. Collaborating with IT teams to define data quality requirements and validate data accuracy after integration or migration.
  
  

Skills:

• Data Governance & Quality Experience Experience with data profiling and analysis.
• Ability to data quality against standards.
• Developing data cleansing processes.
• Experience with building custom data quality rules.
• Ability to train others and educate on data quality best practices.