Data Quality Engineer

BlackStone eIT is looking for a skilled and detail-oriented Data Quality Engineer to join our team. As a Data Quality Engineer, you will play a key role in ensuring the accuracy, completeness, and reliability of our data. You will collaborate with data engineers, data analysts, and other stakeholders to develop and implement data quality standards, processes, and tools. The ideal candidate has a strong understanding of data quality principles, excellent problem-solving skills, and a passion for maintaining high-quality data.

Job Responsibilities

• Collaborate with cross-functional teams to define and implement data quality standards and guidelines.
• Develop and execute data quality tests, measures, and validation processes.
• Identify data quality issues and work with relevant teams to drive their resolution.
• Design and implement data quality monitoring and reporting mechanisms.
• Create and maintain data quality documentation, including data dictionaries and data quality rules.
• Perform data profiling and analysis to identify data quality issues and patterns.
• Collaborate with data governance teams to ensure adherence to data quality standards and policies.
• Provide guidance and support to data stakeholders on data quality best practices and procedures.
• Stay up-to-date with emerging trends and technologies in data quality management and data governance.

Requirements

• Bachelor's degree in Computer Science, Information Systems, or a related field.
• Minimum of 4 years of experience in data quality management or a similar role.
• Strong understanding of data quality principles, including data profiling, cleansing, and validation.
• Experience with data quality tools and frameworks, such as Informatica Data Quality, Talend, or Trillium.
• Proficiency in SQL and data querying languages.
• Experience with data analysis and reporting using tools like Excel or Tableau.
• Knowledge of data governance and data management practices.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.
• Attention to detail and a commitment to maintaining high-quality data.