Data modeling Job Description Template

Data modellers hold the responsibility of defining whole data as how it is organised, structured and accessed. This assures data integrity, and optimizing performance and enhanced data retrieval.


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Data modeling refers to the process of creating a representation of organization data which includes the deployment of various techniques with consistency and accuracy. It includes everything from planning to analyzing modifications. It serves as a foundational base for enabling efficient storage, retrieval, and manipulation of data. Data modeling specialists will play an important role in planning and implementing the whole organization's data structure. The expertise in data modeling will be crucial in assuring the efficiency and scalability of data infrastructure.

Data modeling

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Company Details 

(C.N) is a leading technological firm committed to driving technological innovations and uplifting potential clients through top-notch services. We strive to create opportunities, fulfill aims, and address challenges. With a consistent focus and pushing boundaries, we aspire to create an equitable future through innovative techniques and technology. Data modeling specialists set the high standards through which a company is known for supporting business objectives and decision-making strategies. The expertise will be wonders for organizations to lead to positive outcomes. 

Job Description 

We are actively seeking skilled, dedicated data modeling specialists who will be responsible at the forefront responsibilities in designing, implementing, and crafting data models that support organization objectives and authentic decision-making. 

Effective data will directly support retrieval and authentic data storage. It will empower organizations to harness the full potential of data assets for strategic benefits and operational excellence of the whole business. The candidate will be responsible for consistent efforts toward data integrity and techniques like entity relationship modeling. 

The candidate should be passionate about understanding data needs and translating them into effective models. Data modelers optimize database structures to plan for influential data storage and retrieval, ensuring data consistency and reliability. They work on establishing data governance and compliance. Metadata management, data quality assurance, and data storage are all done by data modelers.  Overall the candidate will be a key aspect enabling the organization to leverage data assets properly for regular insights.  
They ought to be inspiring in addressing difficulties that lead to constructive, significant solutions and a seamless transition to data-driven enterprises.



  • Planning, Developing, and implementing skills that represent the organization's objectives. 
  • Collaborating with stakeholders and understanding needs accordingly. 
  • Optimizing database structures to support storage and retrieval of data efficiently 
  • Should be aware of record keeping and effective resource utilization 
  • Designing a database that enables seamless data flow and stability. 
  • Data consistency across integrated systems 
  • Establishing data governance policies, and procedures to assure privacy and integrity 
  • Compliance with data security plays an important role and Maintaining metadata standards properly
  • Implementing quality data solutions and rectifying errors and inconsistencies.
  • Developing data validation rules, ensuring maintaining high data quality standards. 
  • Implementation of data cleansing processes, and techniques throughout the migration process. 
  • Communicating about technical concepts and solutions. 



  • Should possess a bachelor’s degree in computer science, master's degree also preferred. 
  • Experience in data modeling, database design, and data architecture 
  • Should be proficient in data modeling tools such as ERwin, ER /Studio, and SQL query techniques
  • Entity relationship modeling (ERM ), dimensional data vault. 
  • Familiarity with data governance warehousing concepts, ETL processes, and tools
  • Knowledge of data governance, data quality management, and regulatory standards 
  • Problem solving, analytical skills should be a must 
  • Managing multiple tasks simultaneously with assured timely delivery of projects.
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