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Trainee Cloud Data Specialist

1 week ago

Dubai, Dubai, United Arab Emirates Rackspace Full time

Rackspace Technology offers expertise and managed services across major public and private cloud technologies. We provide Fanatical Experience from first consultation to daily operations. Our experts combine proactive service and expertise with best-in-class tools and automation to deliver technology when needed.

We are looking for a skilled Data Engineering Trainee in Dubai. After an initial period of self-paced onboarding, you will join a high-performing team supporting customers on real-time and batch projects. You will rapidly build knowledge of devops methodologies in data lake development including code management, automated build and testing using pipelines and deployment.

Key Responsibilities:
  1. Collaborate with customers to gather requirements and understand business processes.
  2. Create data pipeline architecture.
  3. Assemble complex data sets meeting functional and non-functional business requirements.
  4. Implement process improvements: automate manual processes, optimize data delivery, re-design infrastructure for scalability.
  5. Build infrastructure for data extraction, transformation, and loading using Spark, SQL, and 'big data' technologies.
  6. Build analytics tools utilizing the data pipeline for actionable insights into customer acquisition, operational efficiency, and key business metrics.
  7. Deploy and monitor system performance in production.
Requirements:
  • Hands-on experience with SQL or Python programming languages.
  • Understanding of Cloud Data Platform Services and Solutions.
  • Knowledge of neural networks, computer vision, language processing, big data processing, or machine learning sub-domains.
  • Familiarity with software configuration management environments and tools like JIRA, Git, Jenkins, TFS, Shell, PowerShell, Bitbucket, etc.
  • Desirable skills include Cloud Computing, AI/Machine Learning, SQL Database Skills, Data Lake Software Skills, Data Modeling Skills, Big Data Software Tools, and Technical Troubleshooting.