Full-time

Responsible for ensuring consistent Data Quality and Metadata Management practices and that those practices are actively followed for prioritized data domains and data activities.

And, when appropriate, actively engaging with Wolter Kluwer teams and acting as a part of their teams to ensure they are able to execute according to Wolter Kluwer’s best practices and data policies.

Essential Duties and responsibilities

Partner with business data teams to :

  • Educate on data quality management practices
  • Recommend data policies which will have a positive effect on data quality
  • Understand data issues / discrepancies and to create actionable remediation plans
  • Identify, define, and document data metrics / KPI’s, implement data quality dashboards on a domain level
  • Provide guidance on how to best design / implement CRUD to ensure high quality data
  • Provide input on roadmaps that allow for optimal iterative development of data models, data CRUD, technologies, etc.
  • Drive the process for defining, documenting and maintain data standards
  • Define process for aligning on the definition of a unique record per domain, and what qualifies as a golden record
  • Report key data quality topics to the data governance council
  • Quantify the value of the data and the data governance artifacts (e.g., data policies, data processes, data standards, etc.

that support that valuation

  • Drive alignment across stakeholders on enterprise data models and definitions
  • Actively participate in key data domain maturity activities to include :
  • Business Glossary
  • Data Dictionary / Catalog
  • Data Profiling and Score Carding
  • Data Cleansing and Standardization
  • Data Dashboard and Reporting

Job Qualifications

Education : Bachelor’s or Master’s degree in information technology, business administration, math, statistics, computer science, or equivalent

Experience :

  • 3 to 5+ years’ work experience in business analysis or data validation related roles collaborating with different parts of the organization
  • Command of data governance and data management best practices, tools and disciplines, business and technology issues related to management of enterprise information assets, and approaches related to data protection
  • Strong technical writing skills capable of taking complex technical concepts and making them easily understood
  • Comfortable working through ambiguous situations to define precise requirements and priorities and drive outcomes
  • Strong understanding of databases and data structures
  • High proficiency in using MS Office in the use of the Microsoft Office Suite of Tools.
  • Prior experience within a Data Governance / Master Data Management Function preferred
  • ERP / CRM / MDM experience as a Data / Business Analyst preferred
  • Information / Collibra experience preferred, but not required

Other Knowledge, Skills, Abilities or Certifications :

  • Enthusiasm for helping team members improve their skills and grow their careers
  • Comfortable working through ambiguous situations to define precise requirements and priorities and drive outcomes
  • Strong process development, planning, tracking and presentation skills
  • Attention to detail, sense of urgency, and commitment to deadlines
  • Strong organizational skills and demonstrated capacity to develop and implement practical strategies, plans and solutions to identified issues and problems
  • Strong analytical skills with the ability to identify quantify and effectively raise business risks associated with data quality or non-compliance
  • High proficiency in using MS Office in the use of the Microsoft Office Suite of Tools.

Travel requirements

Ability to work with and strongly influence remote project teams is expected. Two or three days of domestic travel per month is normal.

There could be international travel as required.

Physical Demands

  • Normal office requirements.
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Responsible for ensuring consistent Data Quality and Metadata Management practices and that those practices are actively followed for prioritized data domains and data activities.

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