Lead Data Management Analyst

• Organize and lead complex companywide initiatives to ensure data quality is maintained
• Oversee analysis and reporting in support of regulatory requirements
• Identify and recommend analysis of data quality or integrity issues
• Evaluate data quality metrics and data quality audits
• Lead project teams and mentor less experienced staff members
• Recommend remediation of process or control gaps
• Serve as relationship manager for a line of business
• Consult with and provide recommendations to senior management regarding data and metadata quality
• Represent client in cross-functional groups to develop companywide data governance strategies
• Build out the WIM Data Catalogue, Taxonomy, Glossary & Dictionary
• Build the conceptual & logical data models across WIM & the linkage to the data catalogue

• 5+ years of Data Management, Business Analysis, Analytics, or Project Management experience
• Strong negotiation and leadership abilities
• Knowledge and understanding of financial services industry: wealth management, brokerage, or retirement
• Knowledge and understanding of Data Models, ERD, Dimensional Models and Metadata
• Relational database experience
• Knowledge and understanding of big data (Hadoop) environment
• XML (Extensible Markup Language) experience
• Experience delivering Business Intelligence (BI), analytics and reporting using API Services architecture
• 5+ years of experience using SQL within a variety of database sources such as SAS, Oracle, or Teradata
• Python experience
• Scripting and automation experience
• Knowledge and understanding of data modeling tools, such as Power Designer
• Strong knowledge of business architecture & wealth management domain
• Experience driving the creation of a data taxonomy & catalogue
• Deep experience of business and metadata semantics, data analysis, data profiling
• Experience with relational databases and big data (Hadoop, S3) as well as with API's (JSON, XML)
• Strong knowledge of Analysis Tools – SQL, Python, Scripting
• Experience with conceptual, logical, and physical data modeling
• Experience with modeling tools - e.g. Power-Designer, Hackolade, Erwin
• Strong Relational and object modeling skills and knowledge of knowledge Graphs
• Experience with auto-harvesting metadata and inferring metadata linkages

Experience with auto-harvesting metadata and inferring metadata linkages