Data Engineer vs. Software Engineer: Career Guide
Due to the novelty of the big data industry, many recruiters often fail to distinguish between a software engineer and a professional big data engineer. Here’s why this mistake can cost you the market position.
Businesses are witnessing a humungous rise in the data. And all of them want to capture the benefits offered by this black opal mine of insights. To do that, corporations need someone who can mine it and claim the responsibilities of leading insights from petabytes of data they find themselves under.
According to a report by the Forrester, 91% of executives say the biggest challenge in leveraging data-based insights is not the tools, but the lack of skills.
While upskilling with big data engineer certification helps data engineers acquire the right industry skillsets, the recruiters also share a part of the blame for the ‘lack of skills impression’ executives have about the big data market. More often than not, recruitment officers make a mistake when hiring for big data engineer professionals. Neither they nor their job descriptions can tell a data engineer from a software engineer.
In many areas of the big data industry, a data engineer’s job can be seen to be handled by a software engineer.
As a result, software engineers, who are not specialized in data engineering, end up with a job that’s complex, overwhelming, and obscure. Are you one of those who confuse a data engineer with a software engineer? Let’s clear the air.
Data Engineer vs. Software Engineer
Software engineering is an umbrella field. Data engineering is one of its sub-field. Data engineers are specialists who fall under that umbrella. You may be wondering that if this is the case, then software engineers should be in a better position to handle the job responsibilities of a professional big data engineer. However, it is not feasible because of the ever-expanding universe of data.
Data has become a significant competitive differentiator in today’s age. If you don’t leverage it, you will be outdone by somebody who does.
This makes the role of big data engineers important. Their jobs have become more nuanced than before, and thus this job category has earned specialized professionals of its own. A quick look at the role of data engineers vs. software engineers.
While a data engineer works with data management systems, a software engineer’s tasks involve developing OS, software designs, back-end development, among others. Unlike big data engineers, software engineers work at a higher-level of policy making, and overseeing all the developments at software front.
A software engineer works with programmers, designers, and other developers, to build software applications and systems the business need.
On the other hand, a data engineer is a specialist in data science. She can make accurate data available to the users, and modify it to enable insights extraction for the benefit of marketing, sales, research, and more.
The field of big data engineering is very dynamic. It requires engineers to keep evolving, update their skills and know-how of tools (say, Hadoop, Hive, Spark, among others) on a regular basis. One can evolve into the role of a data engineer in the Big Data industry from database administrator, data analyst, or data architect.
3 Tasks Data Engineers Do better than Software Engineers
🔗Professionals Big data engineers help companies manage the data and help them analyze the millions of clicks they receive. Here are three domains, which are central to data analysis and management, that helps engineers make recommendations to the taste of end users.
👉Data Modelling
Defining logical relationships between your data is what is largely known as data modeling. It becomes pertinent especially when working with huge unstructured datasets. Recognizing and defining entity type, attributes, rules, and relationships, among other things comes under data modeling.
A software engineer can also create database with some tables. However, a big data engineer can link hundreds and thousands of tables to each other in a fashion that best serves the purpose of analytics. Their expertise comes in handy in determining — how to join the tables such that the existing system doesn’t get disturbed? Which format should the columns be in? How much data replication be done? And more.
Big data engineer certifications also cover the subject of data modeling in detail as it forms a major part of data architecture. Data engineers are better for this function as:
- They can interact with designers and developers to get the right model in place.
- They can iterate a model until the optimal result is achieved.
👉Data Architecture
It is said in the 🔗Big Data industry that businesses must be wise in planning their data architecture. It governs how you collect, store, arrange, and integrate the data. Setting up a robust system although is getting cheaper with new technologies and cloud-based architecture. However, maintaining it still requires expertise (either of in-house or of third-party).
This is one of the crucial skills that can score you even the hardest of data engineering jobs within data science. Gaining these skills is a bit of a hard climb for those without any background in computer science, mathematics, or statistics.
In this job where you may need a team of a database administrator and a few data architects and analysts, a competent big data engineer can fulfill all of these roles.
👉Data Pipelines
It determines the flow of the data. Different departments and people may summon similar data to serve their unit’s purposes. Once in, output data is used for reporting, training of machine learning models, and even decision-making. Thus, for this a stable and accurate data transportation is mandatory for success. Data engineers can ensure not only that data pipelines are in place, but also the consistency of data throughout the pipeline (without any pertinent information leak).
A professional big data engineer understands the input and output data very well. She uses the robust architecture to create efficient data pipelines.
In Conclusion: Should you become a data engineer?
There is little doubt that professionals in the field of data science have a bright future. But equally important is to keep updating oneself, which requires an interest in the field. If you are interested in the work responsibilities of a data engineer, and if you like to organize and manage data to prepare the roadmap for insights, then a career as a Big Data engineer will suit you well.
The dawn of Big Data Engineers is here! Are you ready to bask in its glory?
