Like most careers, being a Data Engineer requires dedication along with understanding of software engineering fundamentals. Having a strong grasp on concepts related to data tied with the ability to program establishes the roots for having working knowledge on being a Data Engineer. Mindset and soft skills are significant when aiming for career growth and progression. Without the ability to navigate there can create stagnation in one’s career. There is a saying, “Data is the new oil”, an ideology derived from so much wealth that is being created through data. The evolution of technology from its primitive state to how we can manipulate, transform and disrupt industries with technology, forecasts a future full of data utilization.
Becoming a Data Engineer can be a fruitful career where the salary is desirable, and the work is fulfilling. The skills required to do the job vary from company to company. Most Data Engineers are working in the cloud, and others are working as Software Database Engineers in the data field and as Database Administrators. Being a good Data Engineer requires Database development skills as well as the ability to create and support data pipelines. Deploying data infrastructures by use of code is also a skill Data Engineers carry which is known as Infrastructure as Code. Overall, a Data Engineer needs to be able to write and manage code which manipulates data using Languages like Python, PowerShell, SQL and other Query Languages. There are many different types of Databases and having a strong understanding on how Databases work is the foundation of being a good Data Engineer. With the evolution of technology, a Data Engineer needs to be able to adapt to new technologies quickly and rapidly. Not learning and being stagnant can be detrimental to a Data Engineers career. Let’s focus on some of the differences between working in the cloud and off the cloud.
Cloud
Working in the cloud allows potentially to work with Big Data. There are 3 cloud providers which dominate cloud services and knowledge in working with one of these cloud providers will give the ability to work with Big Data in most industries. First provider is Azure which is by Microsoft, second is Amazon Web Services (AWS) and Finally Google Cloud Provider (GCP). Concepts and theory regarding the cloud are similar between the three, making it easy to adapt between different providers. Different technologies can use different networking models and thorough learning and research is required for each architecture.
On Premise
When working on-prem the concepts and structure will be exactly the same except you will be working on a Data Center that is owned by the company. Engineers will be responsible to set up the infrastructure and hardware for the company and Developers will connect to the on prem infrastructure for development.
Benefit of Cloud
Unlike on-prem deploying an infrastructure on the cloud can take minutes, while deploying an infrastructure on-prem can take up to 6 months. Cloud provides companies with an immense amount of speed and efficiency. Engineers are able to accomplish so much more in the cloud because any infrastructure or workspace can be deployed almost immediately and the focus can be result based. Working in the cloud also provides a lot of benefits like for most services companies don’t have to worry about managing at the infrastructure level. For most providers and services engineers are responsible at the platform level and the infrastructure is managed by the cloud provider.
Being a Data Engineer will require persistent learning and adapting to new technologies. Having a strong fundamental grasp on programming with data and knowledge on how databases work is essential. Evolution of migrating to the cloud and all the new technologies that are coming into the picture are creating more opportunities as well as growth for Data Engineers. The most important skill and commitment a Data Engineer needs is to constantly learn.
Leave a Reply