How to Become a Big Data Engineer
A Big Data engineer is a very popular and much talked about job profile today as they are incredibly high in demand. If you are interested in math, data, analytics, problem-solving, graphs, numbers, charts, and IT, then a Big Data engineer is possibly the right choice of career for you.
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Big Data
With the advent of social media and the penetration of the internet, several companies have begun generating huge volumes of data. This data could be in the form of structured data like Excel and SQL tables, semi-structured data like email and XML files or unstructured data in the form of images and videos. All these are referred to as Big Data. Essentially, Big Data refers to massive amounts of data that cannot be stored, processed, or analyzed using traditional methods since the quantity of data is too large. To overcome this challenge, various frameworks like Hadoop, Spark, Apache Storm, and Cassandra are used.
Who is a big data engineer?
A professional who develops, maintains, tests, analyses, and evaluates a company’s data is normally called a Big Data engineer. Extremely large sets of data are often referred to as Big Data. All this data is of no use unless it is analyzed and meaningful information is derived from it which in turn improves overall performance. This information is used by organizations to improve their business decisions, products and make their marketing more effective. An engineer plays with the big data and uses it for the organization’s benefit and growth.
Job responsibilities of a Big Data Engineer
Big Data engineers have a variety of responsibilities that range from designing software systems to collaborating and coordinating with data scientists. Some of the responsibilities include:
- Designing, maintaining, implementing, and verifying software systems.
- Building robust systems for ingestion and data processing.
- Using Extract Transform Load operations (ETL)
- Creating data architectures that meet the requirements of the business.
- Researching various ways of obtaining valuable data and improving its quality.
- Mine data from various sources and build efficient data models.
- Collaborating with data analysts, data scientists and other teams.
Also Read: How To Hire A Data Scientist In 2022
Big Data Engineer Vs Data Scientist
The biggest difference is that Big Data Engineers are responsible for building and maintaining the systems and processes that collect and extract data. The role of data scientists is however to analyze the cleaned data and generate insights using various predictive models and create meaningful insights.
Educational Qualifications
A Bachelor’s or Master’s degree in computer science, statistics or business data analytics will be required. You will need to be very skilled in coding, statistics, and data. You will also have to have the following skills:
- Computer programming with languages such as C++, Java, and Python
- Databases and SQL
- ETL and Data warehousing
- Hadoop
- Apache Spark
- Data mining and modeling
- Operating system knowledge for Linux, Unix, Windows, and Solaris
- Talend, IBM DataStage, Pentaho and Informatica
You could also work on getting some professional certifications like:
- Cloudera Certified Professional (CCP) Data Engineer
- Certified Big Data Professional (CBDP)
- Google Cloud Certified Professional Data Engineer
Strong developer skills are required for a Big Data Engineer’s job. Hence, Data engineers need to have a strong programming background. You need to have a love of data or at least an interest in finding patterns in data or it may seem like a boring job. You also must like and have the ability to create systems that are difficult and complex. You need to note that Big Data projects are several times more complex than small data. So, it will be a must that you have a love of data combined with the love of programming to create data pipelines. You need to have an operations mindset and be careful how you build your infrastructure for reliability, so that any changes will not break any of the pieces. A qualified Data Engineer must know the right tool for the job.
Work Experience
Most of the skills required for this role are ideally picked up on the job. Even though you have a degree, anyone with a software background and some experience in operations or systems can make a smooth transition into Big Data Engineering. Data Engineers are responsible for acquiring data for data scientists and data analysts and so they have to migrate it from where it lives and transform it so that it makes sense to the data scientists and data analysts.
Also Read: Data Engineering Skills, Courses And Roles
Social and Communication skills
A Big Data Engineer should have soft skills and certain qualities apart from technical training and certifications.
- Attention to detail: When building data pipelines, data quality is of prime importance. The quality and integrity of the data that you are moving through the pipeline becomes very critical.
- Appreciation for clean design: There is no one way to design and build a pipeline for moving data from Point A to Point B. A good data engineer should appreciate the elegance of clean and simple designs that are not over-architected.
- Good communication Skills: You will have to talk to a lot of people to understand the field before you design anything. You should help customers solve painful problems.
- A love of learning: You must keep learning about new libraries, frameworks and tools in the community. Since things change fast, you will need to quickly learn and update yourself.
Conclusion
Big Data Engineer is a job field that takes a lifetime to master. There will always be something new to learn and you can continue to grow forever. You will need to spend time and effort to keep up with what is happening. If data is your passion, this is the field for you
