Morgan_WM_Data Modelling Professional

2 - 7 years

4 - 12 Lacs

Posted:1 day ago| Platform: Foundit logo

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Work Mode

On-site

Job Type

Full Time

Job Description

  • Minimum 6+ years of hands-on experience working as a full-time Data Modeler.

Role Overview

The Data Modeler will be responsible for designing, developing, and maintaining semantic and relational data models to support enterprise data architecture. The role requires strong technical expertise in database design, data warehousing concepts, and the ability to operate effectively within a global, multi-project environment.

Technical Responsibilities

  • Design and develop semantic data models to support business intelligence and analytics solutions.
  • Apply strong relational database concepts in data modeling and architecture design.
  • Create optimized database designs for Teradata, DB2, and SQL Server environments.
  • Utilize data modeling tools such as PowerDesigner for building and maintaining models.
  • Work with metadata management tools including Metacenter and Collibra.
  • Demonstrate understanding of Hadoop ecosystem and NoSQL database concepts.
  • Support and align data models with Data Warehouse and Business Intelligence frameworks.
  • Ensure data models meet scalability, performance, and maintainability standards.

Analytical and Functional Responsibilities

  • Develop and maintain project deliverables as per defined schedules and timelines.
  • Adapt efficiently to changing requirements and shifting priorities.
  • Work as a self-starter, demonstrating initiative and accountability.
  • Manage and prioritize multiple projects simultaneously.
  • Collaborate with business analysts, application development teams, DBAs, data warehouse, and QA teams.
  • Support global team operations while working independently on assigned tasks.
  • Ensure data model consistency and alignment across business and technical teams.

Key Competencies

  • Strong analytical and problem-solving capabilities.
  • High attention to detail with structured approach to data architecture.
  • Ability to work independently in a fast-paced, global environment.
  • Effective coordination across technical and functional stakeholders.
  • Commitment to quality and timely delivery of data solutions

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