Data Quality Analyst

Onsite presence is required at least once per week. This is an ETL tester role, not a data engineer or developer position. Please do not submit data engineers or developers to this role.

Summary:

The Data Quality Analyst is accountable for the design and operational execution of the Enterprise Information Service Data Quality framework, as well as well as coordination across all technical resources throughout the lifecycle of information investigation and data management. Secondary responsibilities include creation and maintenance of various types of documents, quality assurance testing support and assisting in delivery activities.

GENERAL RESPONSIBILITIES

• Leads Data Quality analysis to support Enterprise Information ServicesData Warehouse projects.
• Work closely with Business Analysts, Data Analysts/Scientists, Development, and Product Owners to ensure data housed in multiple source systems is valid and accurate. Develops validation scripts for automated execution, while creating actionable Data Quality reports that measure trends over time.
• Leads design and implementation of Data Quality screen strategies and protocols used in QA processes; ensures the full application of all relevant QA protocols, processes and procedures across the Enterprise Information Services technology stack.
• Participation in architecting the logical design of Data Quality practices with the technical team, including DQ screen design and specifications, data modeling, and documentation of logical processing flows.
• Act as translator between business and technical community interpreting data domain needs and translating them into more technical quality assessment rules for developers (and vice-versa).
• Business process analysis and data modeling.
• Talend experience is requuired.
• Candidate will be involved in both SQL data investigation and manual testing across multiple scrum teams
• Agile testing knowledge is a plus.
• Develop, documents and implements Data Quality standards for Enterprise Information Services platform.
• Regularly review and interprets QA results and findings with limited support from senior leadership.
• Uses out-of-the-box ingenuity in applying analytical techniques and organizational skills to identifying and evaluating alternatives and to developing recommended approaches to resolving quality assurance issues and problems.