Rackspace Technology seeks a Trainee Data Engineer in Dubai.  After onboarding, you'll join a high-performing team supporting customers on real-time and batch projects. You'll build knowledge of DevOps methodologies in data lake development, including code management, automated build and testing using DevOps pipelines, and automated deployment. Responsibilities include collaborating with customers to gather requirements, creating and maintaining data pipeline architecture, assembling large datasets, identifying and implementing process improvements, building infrastructure for data extraction, transformation, and loading (using Spark, SQL, and big data technologies), building analytics tools, and deploying and monitoring systems. 

Rackspace Technology

Trainee Data Engineer

AWS Support Engineer III

Financial Analyst II

L3 Support Engineer (Windows/Linux on AWS)

L2 Support Engineer (Windows/Linux on AWS)

Support Engineer I - IN (AWS and Linux/Windows)

Client Partner V

Mongo DBA IV

Database Reliability Engineer

Inventory Control Specialist I

<div class="section page-centered" data-qa="job-description"><div><span style="font-size: 16px;">Rackspace Technology is a leading provider of expertise and managed services across all the major public and private cloud technologies. We’ve evolved Fanatical Support to encompass the entire customer journey — providing Fanatical Experience™ from first consultation to daily operations. Our passionate experts combine the power of proactive, always-on service and expertise with best-in-class tools and automation to deliver technology when and how our customers need it.</span></div><div><br></div><div><span style="font-size: 16px;">We are looking for a bright and motivated </span><b style="font-size: 16px;">Trainee Data Engineer</b><span style="font-size: 16px;"> in Dubai. After an initial period of self-paced onboarding, you will join a high-performing team and support customers on real-time and batch projects. You will rapidly build knowledge of the latest devops methodologies in data lake development including code management, automated build and testing using devops pipelines and automated deployment.</span></div></div><div class="section page-centered"><div><h3>Key Responsibilities</h3><ul class="posting-requirements plain-list"><ul><li>Collaborate with customers to gather requirements and to understand their business processes.</li><li>Create and maintain optimal data pipeline architecture.</li><li>Assemble large, complex data sets that meet functional / non-functional business requirements.</li><li>Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.</li><li>Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Spark, SQL and ‘big data’ technologies.</li><li>Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.</li><li>Use tools to deploy and monitor the performance of the systems in production.</li></ul></ul></div></div><div class="section page-centered"><div><h3>Required Knowledge</h3><ul class="posting-requirements plain-list"><ul><li>Some hands-on experience with programming languages such as SQL or Python.</li><li>Base-level understanding of Cloud Data Platform Services and Solutions</li><li>Neural networks, computer vision, language processing, big data processing, or other machine learning sub-domains</li><li>Software configuration management environments and tools such as  JIRA, Git, Jenkins, TFS, Shell, PowerShell, Bitbucket, etc&nbsp;</li><li>Any knowledge of Cloud Computing, AI/Machine Learning, SQL Database Skills, Data Lake Software Skills, Data Modeling Skills, Big Data Software Tools, and Technical Troubleshooting is highly desirable. </li></ul></ul></div></div><div class="section page-centered" data-qa="closing-description"><div>#LI-LP2</div></div>