Data Quality Analyst

The Data Quality Analyst will help the Data Quality Manager in ensuring that data quality is maintained across the enterprise, and as a result enables the Analytics Team to deliver relevant and accurate models and insights. He/She will also help manage and drive action within the enterprise to ensure that data issues are resolved.

Location: YONDU HQ

Status: Urgent

# of Positions Available: 6

Duties and Responsibilities:

  • Support Data Quality Manager in driving data cleansing initiatives to deliver substantial improvements in data quality across the enterprise
  • Deliver communication about the data cleanse activity to the key stakeholders throughout the process.
  • Help in running relevant trainings as well as initiatives to ensure alignment of different data owners to data quality objectives and plans
  • Constantly track initiatives and provide update to Data Quality Manager and Team
  • Escalate project risks and issues to Data Quality Manager
  • Track and Manage Data Quality KPIs across the enterprise
  • Implement and track controls and compliance metrics established and communicated to reduce data issues and improve data quality
  • Automation and publishing of Data Quality KPIs and scorecards for reference of stewards and data owners
  • Assess and conduct RCA / Deep dive analysis with relevant business.
  • Conduct constant testing and experimentation to provide the Data Governance Council with feedback and recommendations for improvements in data management and governance process, standards and guidelines
  • Document key inputs from the data quality and cleansing initiatives

Job Specifications:

  • 3-5 years of experience with data warehouse, MDM, and data integration initiatives or managing enterprise-scale data warehouse or data management projects.
  • Strong SQL knowledge, Java, Talend, Spark, Python
  • Strong understanding of the architecture discipline, processes, concepts and best practice
  • Strong understanding of data tools (cleansing, master data management, metadata, etc.) and data quality policies and procedures