Data Quality Specialist We are seeking a highly skilled and detail-oriented Data Quality Specialist to join our team. The ideal candidate will have expertise in Identity Management (IDM), Comprehensive Data Quality (CDQ), and proficiency in Python programming language. The primary responsibility of this role is to ensure the accuracy, completeness, and consistency of our organization's data assets through the implementation of data quality processes and solutions.
RESPONSIBILITIES
• Uses best practices and tools to analyze and measure data quality and develop action plans to ensure data reliability, completeness, and consistency.
• Develop meticulous action plans based on the findings of data quality assessments to enhance data reliability, completeness, and consistency. These action plans may include implementing data cleansing procedures, establishing data quality rules and standards, enhancing data entry processes, and improving data validation mechanisms.
• Collaborates closely with cross-functional teams including data stewards, data engineers, and business analysts to implement data quality improvement initiatives effectively. This involves fostering a culture of data quality awareness and accountability across the organization.
• Monitors and tracks the effectiveness of implemented data quality measures over time, utilizing key performance indicators (KPIs) and metrics to measure progress and identify areas for further improvement.
REQUIRED SKILLS
• Bachelor of Science in Engineering education.
• Advanced Knowledge of the English language.
• 2+ years of experience. • Must have IDMC/CDQ (Integrated Data Management Console and Customer Data Quality), Python, and ADF (Azure Data Factory) experience, to support RMA projects.
• Should have strong problem-solving skills, a strong attention to detail, excellent analytical and critical thinking capabilities, and the ability to work with large datasets. They should be familiar with data analysis.
• Experience in dealing with the Data Quality principles needed to deliver high-quality data assets.
• Experience with Data Quality tools
• Experience in finding and resolving issues with Data Quality
• Experience with data profiling and data integration tools
