Associate Data Management Analyst

The Data Management Analyst focus specializes in planning, designing, developing and performing assessments on data and structures to ensure integrity, completeness, quality, and appropriateness of formats, records and structures. Uses manual and/or automated methods and procedures to test output as established by product management, client specifications, and business/governance rules.

• Conduct research for quality assessments on data elements and structures to document and evaluate integrity, completeness, quality, and appropriateness of formats, records and structures.
• Configure basic manual and/or automated methods, processes and procedures to test output or input based on data compliance, quality and use requirements as established by product management, client specifications, and governance programs.
• Identify regular and ad hoc reviews, audits, and investigations of data activity and integrity; prepares reports and summaries of findings.
• Support guidelines and documentation of test development processes, procedures and standards.

Education

• Required
  
  
  
  • Bachelor's degree in Computer Science, Information Technology, or a related technical field, or in lieu of related degree, at least 2 years of experience in data management
  
  
• Preferred
  
  
  
  • Related certifications (e.g., Certified Data Quality Professional (CDP), CDMP)
  
  

Skills and Experience

• Required
  
  
  
  • Experience in data quality management field
  • Basic understanding of developing and implementing data quality frameworks, policies, procedures, and controls
  • Familiar with data governance, master data management, and data modeling
  • Basic understanding of SQL, ETL, and data profiling and cleansing techniques
  • Experience in analyzing complex data quality issues, conduct root cause analysis, and develop remedial action plans
    
    
    
    • Technical Skills
      
      
      
      • Data Quality Assessment and Monitoring Tools (e.g., IBM InfoSphere Information Analyzer, Talend)
      • Data Warehousing & ETL Processes
      • Data Analysis Tools (e.g., SAS, R, Python, SSAS)
      • Database Management (e.g., Oracle, Microsoft SQL Server, MySQL)
      • Data Profiling and Cleansing Tools (e.g., DataFlux, Trillium, Informatica Data Quality)