Before we move on to the rest of the sections in this DevOps career guide, it might be worth mentioning some differences between a DevOps Engineer and say a Data Engineer since WeCloudData does offer learning paths and career support for both. Both are exciting careers to embark on and they are both very hot in the job market right now with positions commanding high salaries.
Even though some skills and tools overlap between the two, DevOps and Data engineers serve different purposes in a business and organization. Their toolkits and skill sets start to diverge quite significantly once you specialize and go deeper in the career paths. You will learn more about the tools and technologies employed by a DevOps engineer in a later section, but we will briefly cover them here so you can understand some differences between a Data Engineer and DevOps Engineer.
- Data Engineers focus on designing and implementing data pipelines to ensure the right data flows smoothly from a source to different data consumers including various business units, data scientists, and applications. Their job revolves around data. Any tools they use are for the purposes of ingesting, extracting, processing, and refining data at rest and in motion. Their primary tools to do this include Python, SQL, Spark and Airflow to name a few. The outcomes of their work lead to the business generating insights from raw data. Their work increases the data maturity of organizations bringing them closer to becoming that valuable data-driven company.
- DevOps Engineers focus on the software and application delivery cycle and pipeline. They straddle the development and IT operations worlds because their purpose is to streamline and integrate software development and delivery. Because of their focus, their skills and expertise revolve around software development, IT SysAdmin, and infrastructure practices. They leverage tools and technologies that enable automation throughout the development pipeline and have capabilities to rapidly build up and tear down cloud infrastructures to support applications that customers use directly. Some of the primary tools of DevOps Engineers include Terraform and AWS CloudFormation, Ansible, Jenkins, GitLab, Docker & Kubernetes. The outcomes of their work lead to more rapid application development and feature releases, higher availability, scalability and resiliency of applications, greater automation across IT workflows, and shifts in application architectures such as microservices.
Because their focuses and outcomes differ, in fact, DevOps and Data Engineers complement each other and are extremely valuable to the business when both are present in the organization. The DevOps teams can help boost workflow and application efficiencies and automation for the Data teams who can keep focusing on the organization’s data.
Whether you’re interested in becoming a DevOps Engineer or a Data Engineer, WeCloudData can help. To learn more about the Data Engineer career path and programs please go here. For DevOps, continue reading the rest of this career guide.