ZAIN2476 - Data Platform Engineer Intern

About the Role

We are looking for a fresh graduate to join the Data Analytics & AI Department for a one-year internship contract under Zain Youth Program.


Job tasks and responsibilities:


  1. Support the development, deployment, and monitoring of data pipelines across Cloudera, Apache NiFi, Kafka, Spark, and related platforms.


  2. Assist with troubleshooting data-platform issues by analyzing application logs, system metrics, SQL queries, and data-flow dependencies.


  3. Develop scripts and utilities using Python, SQL, and Linux shell scripting to automate operational and data-processing tasks.


  4. Support data validation, performance optimization, documentation, and controlled deployment of changes across development and production environments.


  5. Work with infrastructure, database, security, and business teams to investigate incidents and deliver reliable data solutions.





What We Need From You

Bachelor's degree in computer science, Data Science, Software Engineering, Computer Engineering, or a related technical field.


Technical skills:


  1. Good foundation in SQL, relational databases, and data-processing concepts.


  2. Working knowledge of Python and Linux command-line environments; shell scripting is an advantage.


  3. Basic understanding of data engineering technologies such as Spark, Hadoop, Kafka, NiFi, Airflow, or similar tools.


  4. Familiarity with APIs, Git, containerization, Kubernetes, or CI/CD concepts is preferred.


  5. Basic understanding of networking, authentication, logging, and systematic application troubleshooting.


Soft skills:


  1. Strong analytical thinking and a structured approach to problem-solving.


  2. Curiosity and willingness to independently investigate unfamiliar technologies.


  3. Clear communication and the ability to document technical findings accurately.


  4. Ownership, reliability, and willingness to follow issues through to resolution.


  5. Ability to accept feedback, adapt quickly, and collaborate across different technical teams.




See also

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