Data Modeler (ONSITE) C2C jobs urgent Need

Role: Data Modeler 
Location: Houston, TX  (ONSITE)

Type: Long Term 

Years of experience needed –

7-12 years of hands-on experience in data modeling, including conceptual, logical, and physical

Experience with data warehousing, ETL processes, and business intelligence environments is preferred.

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Technical Skills:
Proficiency in data modeling tools such as ER/Studio, ERwin, PowerDesigner, Lucidchart, or IBM InfoSphere Data Architect.

Strong knowledge of relational database management systems (RDBMS) like SQL Server, Oracle, MySQL, PostgreSQL, or NoSQL databases

Familiarity with SQL, T-SQL, Python, or other programming languages for data manipulation and automation.glassdoor.comzippia.com

Experience with data warehousing concepts, ETL processes, and dimensional modeling (e.g., star/snowflake schemas).

Understanding data governance, metadata management, and data quality practices.

Design and Develop Data Models: Create conceptual, logical, and physical data models to support business applications, analytics, and reporting requirements. Use modeling techniques such as Entity-Relationship (ER) diagrams, UML, or dimensional modeling

Collaborate with Stakeholders: Work with business analysts, data architects, and other stakeholders to gather and analyze data requirements and translate them into effective data structures.

Optimize Data Systems: Evaluate and optimize existing data models for performance, scalability, and usability, ensuring reduced data redundancy and efficient data flows.

Maintain Data Integrity: Implement data governance practices, including defining naming conventions, standards, and metadata management to ensure consistency, accuracy, and security of data.

Development and Document: Create and maintain data dictionaries, metadata repositories, and documentation for data models to ensure clarity and accessibility across the organization.

Support Data Integration: Collaborate with ETL developers, data engineers, and database administrators to design data flows, source-to-target mappings, and integration processes.

Troubleshoot and Enhance: Analyze and resolve data model performance issues, conduct data quality assessments, and recommend improvements to data architecture and processes.

Stay Current: Keep up to date with industry trends, best practices, and emerging technologies in data modeling, database management