Data Quality Analyst / ETL Tester

• 6-12 month contract
• Hybrid - 2 days/week in Ann Arbor, MI
• SQL queries and ability to analyze data
• Manually test code that is in Talend (their ETL tool)
• Understanding the framework of ETL (Don't need to build code in an ETL)
• Working in DW environment

Some Talend experience specially in DW environment

Minimum Requirements:

• Bachelor s degree with at least 5 years related experience or equivalent combination of education and experience (systems consulting experience desired).
• At least 3 years experience in large scale system implementation efforts following a standard software development lifecycle approach (scrum desired).
• Experience with business and technical requirements analysis, data modeling/mapping, and quality assurance frameworks. Experience with Talend / ETL testing
• Strong oral and written communications skills.
• Ability to create systematic and manual data quality operations procedures in both technical and user-friendly language.
• Demonstrated effectiveness in a fast-paced rapidly changing environment.
• Strong facilitation skills.
• Excellent organization and management skills.
• Extensive knowledge of industry standard development methodologies and technologies.

Job Description:

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 Services Data Warehouse projects.
• Performs ETL testing using Talend
• Business process analysis and data modeling.
• Candidate will be involved in both SQL data investigation and manual ETL testing across multiple scrum teams
• 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).
• 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.