There are many programs and courses at WeCloudData so one might wonder what are the differences between the career paths and job roles – for example, DevOps Eengineer and Data engineer. Both are exciting careers to embark on and they both offer in demand positions with high salaries.
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. We will briefly cover some of these to help illustrate the differences.
Data engineers focus on the design and implementation of data pipelines. 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 leads to the business generating insights from raw data. Their work increases the data maturity of organizations and elevates the business to become a data-driven company.
DevOps engineers focus on the software and application delivery lifecycle. They straddle the development and IT operations worlds because their purpose is to streamline and integrate software development and delivery. Their skills and expertise revolve around software development, IT SysAdmin, cloud and infrastructure. They leverage tools and technologies that enable automation throughout the application development pipeline. Some of the primary DevOps engineering tools include Terraform, 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.
DevOps and data engineers complement each other and are extremely valuable to the business when both are present in the organization. DevOps teams help boost workflow and application efficiencies and automation for data teams who can keep focusing on the organization’s data.