Job Title: Enterprise Data Modeler (Hybrid)
Location: Richmond, VA
Duration: 12+ Months
Job Description:
The client is seeking a senior Data modeler to develop Data models for Data Assets and implementation of a cloud-based data management platform that will support the agency.
Enterprise data modelers provide expert support across the enterprise information framework, analyze and translate business needs into long-term solution data models by evaluating existing systems and working with a business and data architect to create conceptual data models, data flows. Develop best practices for Data Asset development, ensure consistency within the system and review modifications of existing cross-compatibility systems. Optimize data systems and evaluate implemented systems for variance discrepancies and efficiency. Maintain logical and physical data models along with accurate metadata.
Responsibilities:
Skills:
| Skill | Required / Desired | Amount | of Experience |
| Create conceptual data model to identify key business entities and visualize their relationships, define concepts and rules. | Required | 10 | Years |
| Translate business needs into data models Build logical and physical data models for client hierarchy Document data designs for team. | Required | 10 | Years |
| Present and communicate modeling results and recommendations to internal stakeholders and Development teams and explains features that may affect the physical data model. | Required | 10 | Years |
| Develop canonical models, Data as a service models and Knowledge of SOA to support integrations. | Required | 10 | Years |
| Perform data profiling/analysis activities that helps to establish, modify and maintain data model | Required | 10 | Years |
| Analyze data-related system integration challenges and propose appropriate solutions with strategic approach. | Required | 10 | Years |
| Perform data profiling and analysis for maintaining data models Develop and support the usage of MDM toolkit Integrate source systems into the MDM solution | Required | 10 | Years |
| Implement business rules for data reconciliation and deduplication Enforce data models and naming standards across deliverables. | Required | 10 | Years |
| Establish processes for governing the identification, collection, and use of corporate metadata; take steps to assure metadata accuracy and validity | Required | 10 | Years |
| Establish methods and procedures for tracking data quality, completeness, data redundancy, and improvement. | Required | 10 | Years |
| Conduct data capacity planning, life cycle, duration, usage requirements, feasibility studies, and other tasks. | Required | 10 | Years |
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