Enterprise Data Modeler

  • Richmond, VA
  • Posted 4 days ago | Updated 1 day ago

Overview

On Site
Hybrid
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 10 Month(s)
No Travel Required

Skills

Data Modeler
Logical
Physical
Master Data Management/MDM
SQL
Python
R
Azure
Snowflake
Databricks

Job Details

We are looking for candidates for the following direct client position. If you are interested in below position, please forward your updated resume and rate requirement. If you are not interested but know someone who might be, please feel free to forward this email.

Job Title: Enterprise Data Modeler
Location: 1401 East Broad Street Richmond, VA 23219
Duration: 10+ Months

Note:
- local Richmond, VA candidates required
- You will be required to interview ONSITE, NO exceptions
- You will be required to work ONSITE 2-3 days/wk

Skill
Create conceptual data model to identify key business entities and visualize their relationships, define concepts and rules.
Translate business needs into data models Build logical and physical data models for client hierarchy Document data designs for team.
Present and communicate modeling results and recommendations to internal stakeholders and Development teams and explains features that may affect th
Develop canonical models, Data as a service models and Knowledge of SOA to support integrations.
Perform data profiling/analysis activities that helps to establish, modify and maintain data model
Analyze data-related system integration challenges and propose appropriate solutions with strategic approach.
Perform data profiling and analysis for maintaining data models Develop and support the usage of MDM toolkit Integrate source systems into the MDM sol
Implement business rules for data reconciliation and deduplication Enforce data models and naming standards across deliverables.
Establish processes for governing the identification, collection, and use of corporate metadata; take steps to assure metadata accuracy and validity
Establish methods and procedures for tracking data quality, completeness, data redundancy, and improvement.
Conduct data capacity planning, life cycle, duration, usage requirements, feasibility studies, and other tasks.

Thank
Gorak

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