A Big Data Engineer is one of the most talked-about job profiles today. Being a common term, this role enjoys great demand. A Big Data Engineer is undoubtedly a great option for all those inclined to start their careers in the field of Big Data. But, have you ever wondered how to bag this position?
If yes, then look no further. This blog covers all the vital aspects of how to maneuver your way to become a successful Big Data Engineer.
Introduction to Big Data
Before understanding how to become a Big Data Engineer, let’s quickly understand the term ‘Big Data’ first.
Back in the early 2000s, data generation was limited. But with the advent of various social media platforms and multinational companies across the globe, the generation of data has increased by leaps and bounds. According to the IDC, the total volume of global data is expected to reach 175 zettabytes in 2025. That’s indeed a great deal of data.
Below are a couple of statistics from Datafloq and Statista about Big Data and what the future has in store:
Not only is the volume of data increasing, but its velocity is also hitting an all-time high. Having said that, Big Data also refers to data in various formats.
Below are the different types of Big Data:
All this data is termed as Big Data. Big Data refers to massive amounts of data that cannot be stored, processed, and analyzed using traditional old school methods. The quantity is simply too large.
To overcome this challenge of Big Data, various frameworks like Hadoop, Spark, Cassandra, and Apache Storm are used.
Big Data Engineers work towards handling all of this Big Data with the help of these frameworks. Now, with that let’s move on and learn more about this job role and understand how to become a Big Data Engineer.
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Who is a Big Data Engineer?
As mentioned earlier, data generation has increased all across the world. But, it is of no use until it is processed and analyzed competently. Big Data is analyzed to derive meaningful information from it, which in turn improves overall performance. By doing so, organizations can enhance their business decisions, products, and marketing effectiveness. And professionals in the field of Big Data aid this task.
One of the best job roles in this field is that of a Big Data Engineer. Big Data Engineers are professionals who develop, maintain, test and evaluate a company’s Big Data infrastructure. They play with Big Data and use it for the organization’s benefit and growth.
The roles of a Data Engineer and that of a Big Data Engineer are interchangeable. With the rise of Big Data in the data management system, data engineers are also required to handle Big Data. They imbibe Big Data engineer skills for this purpose. Therefore, a data engineer works with several Big Data frameworks and NoSQL databases to manage Big Data.
Let’s go ahead and look into the various responsibilities of a Big Data Engineer, one by one.
Responsibilities of a Big Data Engineer
Big Data engineers have a spectrum of responsibilities starting from designing software systems, to collaborating and coordinating with data scientists. Given below are some of the duties of a Big Data Engineer:
- First and foremost, they are responsible for designing and implementing software systems. They also verify and maintain these systems.
- Big Data Engineers also build robust systems for ingestion and data processing.
- Extract Transform Load operations, known as the ETL process, is carried out by Big Data Engineers.
- They also research various new methods to obtain data and improve its quality.
- Big Data Engineers are also responsible for building data architectures that meet the business requirements. They are responsible for generating a structured solution by integrating several programming languages and tools.
- Their primary responsibility is to mine data from plenty of different sources to build efficient business models.
- Finally, Big Data Engineers work with other teams, data analysts, and data scientists.
Those were just a few of the key responsibilities of a Big Data Engineer. These responsibilities can only be carried out if you have a strong skill set.
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Next up, let’s have a look at the Big Data Engineer skills.
Big Data Engineer Skills
A Big Data Engineer is required to be very skilled in many areas of expertise. Listed below are the top 7 Big Data Engineer skills you will need:
- Programming: Starting off, like most other technology-oriented job roles, out of all the Big Data Engineer skills, programming tops the list. A Big Data Engineer needs to have hands-on experience in any predominant programming language such as Java, C++, or Python.
- Database and SQL: After programming comes the in-depth knowledge of DBMS and SQL. This will help in comprehending how data is managed and maintained in a database. You need to know how to write SQL queries for any Relational Database Management system. Some of the commonly used database management systems for Big Data engineering are MySQL, Oracle Database, and the Microsoft SQL Server.
- ETL and Data warehousing: As mentioned earlier, one of the primary responsibilities of a Big Data Engineer is to carry out ETL operations. For this, you would need to know how to construct as well as use a data warehouse.
As a Big Data Engineer, you will extract data from various sources, transforming them into meaningful information, and loading it into other data storages. Some of the tools used for this purpose are Talend, IBM Datastage, Pentaho, and Informatica.
- Operating System: The fourth skill that you require is knowledge of operating systems. Operating tools are the base for running Big Data tools. Hence a strong understanding of Unix, Linux, Windows, and Solaris is mandatory.
- Hadoop tools and frameworks: You must have experience with Hadoop based analytics. Hadoop is one of the most commonly used Big Data engineering tools, so it's understood that you need to have experience with Apache Hadoop based technologies like HDFS, MapReduce, Apache Pig, Hive & Apache HBase.
- Apache Spark: The sixth skill that you require, is to have worked with real-time processing frameworks like Apache Spark. As a Big Data Engineer, you will be dealing with enormous volumes of data, so for this, you need an analytics engine like Spark, which can be used for both batch and real-time processing. Spark can process live streaming data from several sources like Twitter, Instagram, Facebook, and so on.
- Data mining and modeling: The final skill requirement requires you to have experience with data mining, data wrangling, and data modeling techniques. Data mining and data wrangling include steps to preprocess and clean the data using various methods, find unseen trends and patterns in the data, and make it ready for analysis.
Big Data Engineers examine massive pre-existing data to discover new insights through data modeling. Some of the tools used for this are Python, R, Rapid Miner, Weka, and KNIME.
So, those were some of the skills required for you to become a Big Data Engineer. Going ahead, let’s have a look at the career prospects for a Big Data Engineer.
Roadmap on How to Become a Big Data Engineer?
Career opportunities in the field of Big Data are endless as organizations rely on Big Data for crucial decision making.
The average salary of a Big Data Engineer in the U.S is around $90,000 and ranges from $66,000 - $130,000. In India, the average salary is around Rs.7,00,000 and ranges from Rs.400,000 – Rs.14,00,000.
In addition to the job role of a Big Data Engineer, there are a few more job profiles in this field, they are - Data architect, BI Architect, and Senior Big Data Engineer.
To sum up the entire process on how to become a Big Data Engineer, let's look at the roadmap below:
Fig: How to become a Big Data Engineer?
As seen from the above roadmap, first, you need to complete your graduation and also fulfill the required skill set mentioned in Big Data Engineer skills. In addition to this, what can set you apart from the rest, is a Big Data certification course.
If you are looking to become a Big Data Engineer, you can take up a few certifications, which will act as a catalyst in your transition to becoming a Big Data Engineer. Few relevant certifications a Big Data Engineer can opt for are:
- CCP Data Engineer
- IBM Certified Data Architect – Big Data
- Google Cloud Certified Data Engineer
- Big Data Master's Program from Simplilearn
So now, you must be wondering how Simplilearn can help you?
If you're looking to make a career in the Big Data and Hadoop field, then the Big Data Engineer Master's Certification program, in collaboration with IBM provided by Simplilearn, will be a good fit. There are seven modules in this valuable course.
You can learn about Big Data, Spark, PySpark, MongoDB, Cassandra, Scala, and others. Also, some of the essential tools covered in this course are Hadoop, Apache Spark, MongoDB, and Casandra, to name a few. If you want to enroll for this course and start your career in Big Data, click on the following link: Big Data Engineer Master’s Program.
Fig: Big Data Engineer Master’s Program
Simplilearn's Professional Certificate Program in Data Engineering, aligned with AWS and Azure certifications, will help all master crucial Data Engineering skills. Explore now to know more about the program.
Are You Ready to Become a Big Data Engineer?
Reading this article, you had a brief introduction to the world of Big Data. Such as who a Big Data Engineer is, the various responsibilities of a Big Data Engineer, and Big Data Engineer skills. You also saw a roadmap on how to become a Big Data engineer.
In addition to that, now you know exactly how Simplilearn can help you achieve your dream and kickstart your career in Big Data engineering By completing Data Engineering Certification Program.
Do you have any questions for us concerning ‘How to become a Big Data Engineer’? Please mention them in the comment section of this article. Our qualified experts will get back to you as soon as possible!
