Enterprise Data Modeler

Role: EnterpriseData Modeler

Location: Richmond,VA (Need local)

JobDescription:

The clientis seeking a senior Data modeler to develop Data models for Data Assets andimplementation of a cloud-based data management platform that will support theagency.

EnterpriseData Modeler provides expert support across the enterprise informationframework, analyse and translate business needs into long-term solution datamodels by evaluating existing systems and working with a business and data architectto create conceptual data models , data flows . Develop best practices for DataAsset development, ensure consistency within the system and reviewmodifications of existing cross-compatibility systems. Optimize data systemsand evaluate implemented systems for variance discrepancies and efficiency.Maintain logical and physical data models along with accurate metadata.

Responsibilities:

Create conceptual data model to identifykey business entities and visualize their relationships, define concepts andrules.

Translate business needs into data modelsBuild logical and physical data models for client hierarchy Document datadesigns for team.

Present and communicate modeling resultsand recommendations to internal stakeholders and Development teams and explainsfeatures that may affect the physical data model.

Ensure and enforce a governance process tooversee implementation activities and ensure alignment to the definedarchitecture.

Perform data profiling/analysis activitiesthat helps to establish, modify and maintain data model.

Develop canonical models, Data as a servicemodels and Knowledge of SOA to support integrations.

Analyze data-related system integrationchallenges and propose appropriate solutions with strategic approach.

Perform data profiling and analysis formaintaining data models Develop and support the usage of MDM toolkit Integratesource systems into the MDM solution Implement business rules for datareconciliation and deduplication Enforce data models and naming standardsacross deliverables.

Establish processes for governing theidentification, collection, and use of corporate metadata; take steps to assuremetadata accuracy and validity.

Establish methods and procedures fortracking data quality, completeness, data redundancy, and improvement.

Conduct data capacity planning, life cycle,duration, usage requirements, feasibility studies, and other tasks.

Create strategies and plans for datasecurity, backup, disaster recovery, business continuity, and archiving.·Ensure that data strategies and architectures are in regulatory compliance.

Good knowledge of applicable data privacypractices and laws.

Strong written and oral communicationskills. Strong presentation and interpersonal skills and Ability to presentideas in user-friendly language.

Experience in writing queries (SQL, Python,R, Scala) as needed and experience with various data technologies such as AzureSynapse or SQL Server, Snowflake, Databricks