
Data Modeler
3 days ago
We are seeking an experienced Data Modeler with a strong background in real estate, investment management, and master data management. The ideal candidate will be responsible for designing, implementing, and maintaining data models that support our business objectives. This role requires a deep understanding of data architecture, data integration, and database optimization.
Key Responsibilities:
Design and Develop Data Models:
Create conceptual, logical, and physical data models to support business requirements in the real estate and investment management domains.
Master Data Management (MDM):
Develop and manage master data solutions to ensure data consistency, accuracy, and reliability across the organization.
Data Integration:
Integrate data from various sources, ensuring consistency and accuracy across systems.
Data Mapping:
Map data elements to business requirements and create detailed data mapping documents.
Collaboration:
Work closely with data analysts, database administrators, and business stakeholders to understand data needs and deliver solutions.
Documentation:
Maintain comprehensive documentation of data models, data flows, and data dictionaries.
Data Governance:
Ensure data models comply with data governance and security policies.
Qualifications:
Experience:
Overall 12+ Yrs
Minimum of 5 years of experience in data modeling, with a focus on real estate, investment management, and master data management.
Technical Skills:
Proficiency in SQL, data modeling tools (e.g., ER/Studio, ERwin), and database management systems (e.g., Oracle, SQL Server).
Domain Expertise:
In-depth knowledge of real estate and investment management processes and data requirements.
MDM Expertise:
Strong experience in master data management, including data governance, data quality, and data stewardship.
Analytical Skills:
Strong analytical and problem-solving skills.
Communication:
Excellent verbal and written communication skills.
Preferred Skills:
- Experience with data warehousing and business intelligence tools.
- Familiarity with cloud-based data solutions (e.g., AWS, Azure).
- Knowledge of data governance frameworks and best practices.
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