Data Modeller

Job Summary

We are seeking a skilled Data Modeler to join our data management team. The Data Modeler will design, implement, and maintain conceptual, logical, and physical data models to support business intelligence, analytics, and operational systems. This role involves collaborating with cross-functional teams to ensure data models align with organizational goals, optimize data storage and retrieval, and maintain data integrity and consistency. The ideal candidate will have strong technical expertise in data modeling tools, database management systems, and a deep understanding of business processes.

.

Years of experience needed –

• 5-12 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.

.

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, and analytics.usebraintrust.com

Qualification:

• Education: Master’s or bachelor’s degree in computer science, Information Systems, Data Science, Applied Mathematics, or a related field.