Top 20 C2C jobs Data Modeler Jobs with Regulatory Compliance Mount Laurel NJ (Onsite) Quick Apply

Data Modeler

A Data Modeler plays a crucial role in designing and managing data structures to ensure effective data management within an organization. Here are the top 20 job responsibilities of a Data Modeler:

1. Requirements Analysis: Collaborating with stakeholders to gather and understand data requirements for various business processes. Data Modeler
2. Data Modeling: Designing conceptual, logical, and physical data models that align with business requirements and industry standards. Data Modeler
3. Normalization and Denormalization: Applying normalization techniques to optimize data storage and denormalization when necessary for query performance.
4. Database Design: Creating and maintaining database schemas, tables, views, and relationships based on the data model. Data Modeler
5. Data Dictionary Maintenance: Developing and maintaining a data dictionary to document data elements, definitions, and relationships.
6. Metadata Management: Managing metadata to provide a comprehensive view of the data and its lineage.
7. Data Quality Assurance: Defining and implementing data quality standards and ensuring adherence to those standards.
8. Collaboration with Stakeholders: Working closely with business analysts, developers, and database administrators to ensure alignment with business goals.
9. Performance Tuning: Optimizing data models for query performance and collaborating with database administrators to enhance database performance.
10. Data Migration: Designing and overseeing data migration processes to ensure the smooth transition of data between systems.

1. Change Management: Managing changes to the data model and ensuring that any modifications are well-documented and communicated.
2. Data Security: Collaborating with security professionals to ensure that data access and storage adhere to security policies and regulations.
3. Data Integration: Collaborating with ETL developers to design and implement effective data integration processes.
4. Tool Proficiency: Using data modeling tools proficiently to create and manage data models efficiently.
5. Data Governance: Participating in and promoting data governance initiatives to ensure data quality, security, and compliance.
6. Training and Documentation: Providing training to team members and creating documentation for data modeling processes and standards.
7. Data Lineage: Establishing and maintaining data lineage to track the flow of data from source to destination.
8. Data Analysis Support: Supporting data analysts by providing well-structured data models for their analytical needs.
9. Collaboration with Architects: Collaborating with enterprise architects to ensure alignment with overall enterprise architecture and strategy.
10. Continuous Learning: Keeping up-to-date with industry trends, emerging technologies, and best practices in data modeling.

These responsibilities may vary based on the organization’s size, industry, and specific data management needs. The goal is to ensure that the data model effectively supports the organization’s business objectives and facilitates data-driven decision-making.