In this age of rapid technological advancement, more and more businesses are growing and expanding online over the past decade. When everything’s online, that just means scores and scores of data. And with the amount your online business is and will be facing in the not-so-distant future, you will need technology and the skills of professionals to help you with processing, organizing, and analyzing this data.
The thing about data is that you can’t just give it to anyone. Data is a sensitive matter and you want to be giving them to professionals who know what they are doing.
The question is: who should you hire? With so many specializations and roles in IT being talked about online and offline, it can get a little confusing. You may find yourself asking if there’s even a difference between all of them. Trust us, there is—just like there is a clear difference between coding and programming.
Let us ease your hiring woes for you as we differentiate between data engineers and machine learning engineers and why hiring one (or both) of them can benefit your online business.
Data Engineers
When thinking about data-related professions, the first thing that comes to mind for most people is being a data scientist. What makes data engineers different is their responsibility to deliver the infrastructure and framework to process the data that you have. Data scientists, on the other hand, create the model or algorithm that will help you in using data in a more practical way such as automating your tasks.
Think of data engineers as architects—business intelligence architects to be precise. Data engineers have a solid grip on business intelligence tools. They also manage the database they create to make sure that everything is working like a well-oiled machine. This is so that you and anyone with the right authority can easily access desired data or information that is contained in the database.
Some of the other responsibilities of data engineers are collecting, moving, and storing data. They also prepare that data for further usage in the near future. The work of data engineers is very important as they’re the ones developing the foundation that will then be further improved by data science or machine learning processes.
A Data Engineer’s Tool Belt
Data engineers are well-versed in the following:
- Python
- SQL
- Has knowledge in Java or Scala
- Has knowledge in cloud services such as Google Cloud or Amazon Web Services
These are the basic skills that a data engineer will surely have, but this can be further enhanced with tools and frameworks such as Tableau, Kafka, Hadoop, and Spark.
What Data Engineers Can Do For Your Business
Data engineers are usually the first people you hire especially when you’re just starting out or in the midst of your business’ growth and you already have a bulk of data in front of you. They will design an infrastructure that will enable your company to store and process data effectively so that you can retrieve them easily whenever you need to.
Data engineers can also help out in terms of streamlining data science workflows. This will further add value to your product offerings and build out retention models as well as customer lifecycles.
Furthermore, your data engineers will work very closely with your data science and business intelligence teams in that they will create pipelines for processes such as research, reporting, and even machine learning.
Machine Learning Engineers
Machine learning engineers are usually multifaceted. They are highly skilled programmers with knowledge of both data engineering and data science. Machine learning engineers use big data tools and programming frameworks to make sure that the raw data gathered from the data pipelines (which were laid out by data engineers) are redefined as data science models. These models are typically ready to scale to fit your growing online business.
If data engineers build and define the infrastructure, it’s the machine learning engineers that are feeding data into it. It’s the machine learning engineers that also build programs or algorithms that control bots and computers to ease your business processes.
A Machine Learning Engineer’s Tool Belt
Machine learning engineers combine the skills of both data scientists and data engineers. Basically, the tools stated above plus programming languages such as R, C++, C, JavaScript, Scala, and Julia and programming tools such as MATLAB.
They should also be experienced in distributed systems tools like consul, zookeeper, and Etcd.
What Machine Learning Engineers Can Do For Your Business
The role of machine learning engineers in your business will depend on the project they will be working on. Aside from developing machine learning models, they also collaborate with data engineers to create data and model pipelines.
Machine learning engineers are also typically involved in the entire lifecycle of data. This includes research, design, experimentation, development, and subsequently, deployment, monitoring, and maintenance.
Furthermore, they will be responsible for researching and implementing best practices to enhance the machine learning infrastructure you have in place.
The amount of data you have now will only multiply as you grow your online business. Choosing between hiring a data engineer or a machine learning engineer will greatly depend on your business model and what stage your business is in right now. You might even need both if you’re growing at a very rapid pace.
However, what’s certain is that these people who are highly skilled in everything data and what to do with it will definitely help you as you expand and improve your online business.
Are you looking for Data or Machine Learning Engineers for your business, give us a call or send us a message for a free consultation.
