Data Modeler

Education : Master’s degree in Computer Science, Data Science, Information Systems, or a related field (must have) Job Summary :

This job requires relocations to Saudi Arabia for 12 months. We are seeking an experienced

Data Modeler

to design and maintain scalable, standardized, and business-aligned data models for SST and analytics initiatives within a leading telecom organization. The ideal candidate will have a strong background in telco data modeling, excellent collaboration skills, and the ability to drive consistency across various data domains, including CVM, AI, and reporting. Key Responsibilities :

Design and maintain

conceptual, logical, and physical data models

to support SST and analytics initiatives. Define and manage

standardized telco-wide entities

such as customer, usage, and billing data. Ensure

data consistency and alignment

across CVM, AI, and reporting use cases. Collaborate with

integration experts

and

data analysts

to evolve schema designs based on business and technical needs. Maintain and optimize data models for

performance, scalability, and reusability . Align data modeling practices with

industry standards

and internal governance policies. Required Skills & Qualifications :

5–8 years

of hands-on experience in data modeling, including conceptual, logical, and physical modeling. Proven experience working in the

telecommunications industry

with deep understanding of telco-specific data entities. Proficiency in

data modeling tools

such as ER / Studio, Erwin, or similar. Familiarity with

data warehousing, ETL processes , and

data governance principles . Strong knowledge of

relational and non-relational database systems

(e.g., Oracle, SQL Server, PostgreSQL, NoSQL). Excellent communication and

collaboration skills , with the ability to work cross-functionally with technical and business teams. Preferred Qualifications :

Experience with

big data platforms

(e.g., Hadoop, Spark) and cloud data environments (e.g., AWS, Azure, GCP). Knowledge of

AI / ML workflows

and how data modeling supports predictive analytics.

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