Data Quality Analyst

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Written by AI from the job title and company, not by Crowe Global, so some details may not match this job. The employer's own page has the real description.

Overview

The Data Quality Analyst at Crowe Global will play a crucial role in ensuring the integrity and accuracy of data across various platforms. This position involves analyzing complex datasets, identifying discrepancies, and implementing data quality improvement initiatives. The analyst will collaborate with cross-functional teams to establish data standards, develop quality control processes, and produce regular reports on data quality metrics. A strong emphasis will be placed on leveraging analytical skills to support business decisions and enhancements based on data insights.

Job Responsibilities

• Conduct regular audits of data to ensure compliance with established quality standards.
• Identify and rectify data quality issues through detailed analysis and testing.
• Develop and maintain data quality metrics and key performance indicators (KPIs).
• Collaborate with IT and business units to define data requirements and improve data processes.
• Create, document, and implement data quality improvement plans and processes.
• Prepare comprehensive reports and presentations on data quality findings for stakeholders.
• Provide training and support to team members regarding data quality best practices.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Statistics, or a related field.
• Minimum of 3 years of experience in data quality analysis or a similar role.
• Proficient in SQL and data manipulation techniques.
• Strong analytical and problem-solving skills with keen attention to detail.
• Experience with data profiling, data cleansing, and data migration processes.
• Excellent communication skills, both verbal and written.
• Ability to work effectively both independently and as part of a team.

Technologies & Tools

The Data Quality Analyst will utilize a variety of technologies and tools to enhance data quality standards. The primary tools include SQL for data manipulation and querying, data visualization software such as Tableau or Power BI for reporting purposes, and data management platforms like Informatica or Talend. Additionally, familiarity with statistical analysis software (e.g., R or Python) will be beneficial for advanced data analytics tasks.

Ideal Candidates

The ideal candidates for the Data Quality Analyst position will possess a strong analytical mindset combined with a detail-oriented approach to data management. They should demonstrate resilience in diagnosing data anomalies and proactively suggesting improvements. Possessing excellent interpersonal skills is essential, as effective collaboration with various departments will be fundamental to success. A passion for data integrity and a commitment to driving quality standards will also be key attributes of successful candidates.