Key Responsibilities:
- Design, implement, and maintain scalable data pipelines for the extraction, transformation, and loading (ETL) of large datasets
- Create algorithms and statistical models to extract actionable insights.
- Design, develop and implement data models for base tables and dashboards
- Conduct thorough analysis to understand data models, upstream source systems, and trends within datasets
- Query massive data sets to interpret complex relations
- Build complex logics for attributes, metrics and feature banks under engineered datasets and reports
- Leverage GenAI capabilities and machine learning techniques to enhance data analysis capabilities.
- Enable and/or develop AI use cases (ML or GenAI based)
- Test, vet, deploy, maintain and monitor AI pipelines
- Create visualizations and dashboards to communicate data-driven insights.
- Package and serve data products over the various reporting outlets in use
- Adhere to information security and personal data privacy mandates and guidelines in data collection, analysis, access management and reporting
- Implement best practices for data governance, quality and documentation
- Implement best practices and continuously improve data analytics processes
- Develop and maintain data architecture and data management, ensuring data integrity, security, and optimal performance
Education:
Bachelor's degree in IT, Computer Engineering, Computer Science, Data Science
Level of Experience:
Limited Experience (2-5Yrs) in a related field
Technical Skills & Knowledge:
Essential:
- Excellent knowledge of data warehousing and data modelling principle
- Excellent knowledge SQL
- Very good knowledge of Linux and OS Administration
- Excellent knowledge of Python
- Working knowledge of orchestration platforms (e.g. Airflow)
Desirable:
- Good knowledge of telecom core systems and data sets
- Good knowledge of key information security and networking principles
- Good knowledge of Scala
- Good knowledge of spark framework
Certifications & Licensure
Essential:
- SQL (any variant) Certification
- Python Certification
- Hadoop or Data Lakehouse Certification
Desirable:
- GenAI and LLM Engineering Certification
- Spark Certification
- Airflow Certification
Tools & Systems:
Essential:
- Data Warehousing or modern data platform
- Apache Hadoop eco-system
- Power BI (or other visualization tools)
- Python (base, pandas, scikit-learn)
- Agentic Development
Desirable:
- GenAI e2e solutions development
Skills Required
- Bachelor’s degree in IT, Computer Engineering, Computer Science, or Data Science
- 2–5 years of experience in a related field
- Excellent knowledge of data warehousing and data modeling principles
- Excellent knowledge of SQL
- Very good knowledge of Linux and operating system administration
- Excellent knowledge of Python
- Working knowledge of orchestration platforms such as Airflow
- SQL certification
- Python certification
- Hadoop or Data Lakehouse certification
- Knowledge of telecom core systems and datasets
- Knowledge of information security and networking principles
- Knowledge of Scala
- Knowledge of Apache Spark
- GenAI and LLM Engineering certification
- Spark certification
- Airflow certification
- Experience with data warehousing or modern data platforms
- Experience with the Apache Hadoop ecosystem
- Experience with Power BI or other visualization tools
- Experience with Python libraries including pandas and scikit-learn
- Agentic development experience
- GenAI end-to-end solutions development experience
What We Do
Umniah is a leading Jordanian mobile network operator and telecommunications company providing high-quality mobile, internet, and digital solutions. Established in 2005 as a subsidiary of Batelco Group, it focuses on innovation and customer experience, offering services to millions of customers and businesses across Jordan through its mobile, fiber, and cloud computing capabilities.







