RESPONSIBILITIES

1. Seven (7) years IT work experience with five (5) years in quality assurance and/or data management required.
2. Expertise with data quality tools for data profiling, cleansing and standardization preferred.
3. Experience in implementing solutions and processes for master data and hierarchy synchronizations preferred.
4. Must have a solid understanding of logical database design principles.
5. Understand the methodologies and technologies that depict the flow of data within and between technology systems and business functions/operations.

6. Participate in the development of short- and long-term information architecture strategies, support and participate in the strategic planning process.  Build data migration strategies.

7. Provide support for master data management (MDM) system development, implementation and maintenance.  Participate in establishing governance for metadata management across the enterprise.  Develop metadata integrity processes. Participate in the governance activities associated with ensuring compliance with the enterprise information/data architecture.  Work with IT teams to ensure compliance.  Perform regular audits of data.

8. Work with business and vendor partners, and project delivery leads to determine business data intelligence needs.  Interpret and document the data needs for the business.  Analyze program needs and translate them into data warehousing and data mart requirements.

9. Work in partnership with data architects to design the common customer view of information.  Create and implement detailed specifications for metadata repository solutions.  Manage the data dictionary.  Define, document, and maintain all data definitions, data sources, business meaning and usage of information.  Develop single source data strategy. Research internal and external data sources for new data and better sources of data feeds. Identify and validate opportunities to share/reuse existing data/information.  Direct the production of regular reports and analysis on data. 

10.Create a framework for representing the data elements including the entities, relationships and attributes.  Recognize and resolve conflicts between models, ensuring that data models are consistent with the enterprise model (e.g., entity names, relationships and definitions).  Support the effort for high level modeling of key program processes and key data entities.  Ensure integration of the project logical data model into the enterprise conceptual data model and that physical models align with the logical data model.

11.  Develop solutions and recommendations for improving data integrity issues.  Analyze data issues and works with development teams for problem resolutions. Identify problematic areas and conduct research to determine the best course of action to correct the data, identify, analyze and interpret trends and patterns in complex datasets.

12.  Research and resolve business-critical production problems/system abends.

13.   Establish data profiling and preventative procedures to improve data quality.  Create data quality metrics for identifying data related issues. Collaborate with multiple teams to establish appropriate data access management.

14.   Ensure technical documentation is developed and maintained.

15.   Assist in the coaching and training of customers in the use of business intelligence tools to enhance business decision-making capability.  Work with project teams to understand the business environment in order to manage enterprise-wide information/data support systems.  Provide guidance on complex issues to other team members.

16.   Provide leadership, coaching and mentoring to team members.  Provide performance feedback to managers, as needed.