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Data Quality Analyst (Strong SQL, ETL tools & Testing - Manual is ok) - Contract

Job Title
Data Quality Analyst (Strong SQL, ETL tools & Testing - Manual is ok) - Contract
Job ID
Ann Arbor,  MI 48104
Other Location

Title:  Data Quality Analyst (Strong SQL, ETL tools & Testing - Manual is ok)

Our History:
From our start in 2009, Conexess has established itself in 3 markets, employing nearly 200+ individuals nation-wide. Operating in over 15 states, our client base ranges from Fortune 500/1000 companies, to mid-small range companies. For the majority of the mid-small range companies, we are exclusively used due to our outstanding staffing track record

Who We Are:
Conexess is a full-service staffing firm offering contract, contract-to hire, and direct placements. We have a wide range of recruiting capabilities extending from help desk technicians to CIOs. We are also capable of offering project based work.

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.

Minimum Requirements:

  • Bachelor’s degree with at least four to seven years related experience or equivalent combination of education and experience (systems consulting experience desired).
  • At least three 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.
  • 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.
  • Talend and SQL Server experience are preferred
  • Strong SQL skills
  • ETL testing experience (manual testing is ok)
  • Understanding/foundation of ETL tools – any
  • Soft skills – team player, ability to multi task

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.
  • 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.


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