Data Quality Analyst

As a Data Quality Analyst, your primary responsibilities include meticulously analyzing large datasets to identify data inconsistencies, errors, and anomalies. You will be tasked with conducting comprehensive data audits and validations to ensure that all data entering the system adheres to established standards and protocols. This involves developing and implementing data quality best practices and procedures to enhance data accuracy, completeness, and reliability. By employing various data cleansing techniques, you will correct any identified issues and continually monitor data for accuracy. Additionally, collaborating with data engineers and other stakeholders, you will provide insights and recommendations for improving data processes and infrastructure to support seamless data management and utilization.

Beyond data cleansing and auditing, a critical responsibility is the continuous evaluation and enhancement of the organization's data quality frameworks. You will create and maintain detailed documentation of all data quality metrics and processes to ensure transparency and accountability. Furthermore, you will regularly communicate your findings and progress to relevant stakeholders, offering actionable recommendations to address any data quality issues that arise. By fostering a proactive approach to data quality management, you will play a crucial role in supporting the organization's business intelligence and analytics initiatives, ensuring that data-driven decisions are based on accurate and reliable information.

For a Data Quality Analyst role, recommended studies typically include a bachelor's degree in computer science, information technology, data science, or a related field. Advanced certifications like Certified Data Management Professional (CDMP), Project Management Professional (PMP), or Certified Information Systems Auditor (CISA) are highly valued. Practical knowledge of data management platforms, SQL, and data warehousing tools is essential. Additionally, familiarity with data quality tools such as Informatica Data Quality, Talend, or Trifacta, and proficiency in statistical analysis software like SAS or R can significantly enhance your expertise in this domain.