How to become a Big Data Engineer

Big Data is referred to as a huge data set with massive volume.

Big Data includes both data type, structured and non-structured. The main issue with Big Data is that huge data is difficult to process using software techniques and traditional databases. It comes from several different sources such as text, audio, images, and videos. Data is always available online, and it is gathered and created by digital technologies such as apps on phone, social media interaction or e-shopping, etc. All these data are mixed with other sources of data and tend to become Big Data.

Hence Big Data helps you to understand your buyers and customers; they also help you to understand their interests and behaviors.

For this purpose, companies access your social media, browser logs, history, texts, and sensor & sensitive data to get more and more information about you. Just like Big Data is watching our daily life taking notes from it and sell information to other companies which later affect our day to day living.

Businesses and organizations use big Data for finding trends and patterns about humans and their way of interacting with tech. Which can be later used to make profitable decisions and maximizes business at best.

Who is Big Data Engineer

We can say that Big Data is the hottest job of 2019; it not only projects the highest salary in the tech world also innovate solutions that are the most interesting part of their job. But wait, who is Big Data Engineer?

Big Data Engineer comes right after Big Data Architect because he builds whatever Big Data Architect has designed. They are hired for developing, testing, and maintaining Big Data solutions within the boundary of the organization. They are also involved in designing of Big Data solutions because the company wants their expert opinion Hadoop based technologies such as MapReduce, Hive MongoDB or Cassandra.

A Big Data Engineer must-have a software engineering degree from any reputable university along with it he must also get the best data science certification 

There is petabyte or even Exabyte of data to be dealt with every day, and Big Data Engineer must be prepared to handle huge data with big volume. He must know how to solve Big Data problems and provide Big Data solutions.

Big Data Engineer works on huge and complex projects; he knows to collect, analyzing, parsing, managing and visualizing data. So that he can convert raw data into knowledge.

Jobs that are similar to Big Data include;  Chief Data Officer, Big Data Manager, Big Data Scientist, Big Data Analyst, Big Data Solutions Architect, Big Data Visualizer, Big Data Consultant, and Big Data Researcher.

Become a Big Data Engineer

Essential Things Data Engineers should know by heart

So if being a Data Engineer is your career choice, then initially, you should know what is what? There are certain steps.

First of all, you should know it is a field of computer science. So that you must know algorithms and data structures. Secondly, since Data Engineers work with data, it is necessary for them to have an understanding of database operations and structures.

1.      Algorithm and Data Structures

We all have learned data structures and algorithms at university and schools. Hence Data engineers must use perfect data structure, which will drastically improve the performance of the algorithm.

Below is the list of online courses where you can learn data structures and algorithms

  • Easy to Advanced Data Structures
  • Algorithms, Part I
  • Algorithms, Part II

Also, read classic work by Thomas Cormen ---  Introduction to Algorithms.

You can also have online YouTube tutorials by Carnegie Mellon University;

  • Intro to Database Systems
  • Advanced Database Systems

2.      Learn SQL (Structured Query Language) 

Data Engineer spent his whole life with data, and SQL is the language of data, or it is lingua franca of data. It helps you to request information from the database.

If you have a background in development, you know how important is to learn SQL. Well thee purpose of mentioning SQL here is that all huge Big Data warehouse supports SQL:

  • Amazon Redshift
  • HP Vertica
  • Oracle
  • SQL Server and other

SQL engines like Apache Hive, Impala, etc. were invented to analyze a huge layer of data stored in distributed systems like HDFS.

One should start learning SQL from online sources;

  • Intermediate SQL
  • Joining Data in SQL


Python, Java, and Scala are the best programming languages for Big Data Engineers.

JAVA and SCALA are programming languages in which tools for processing and storing huge amounts of data are written. Such as,

  • Apache Kafka (Scala)
  • Apache Cassandra (Java)
  • HBase (Java)
  • Hadoop, HDFS (Java)
  • Apache Spark (Scala)
  • Apache Hive (Java)

SCALA allows you to resolve problems like parallel data processing. These three have a better approach to problem-solving.

4.      Tools for Big Data

Big Data popular tools are,

  • Apache Spark
  • Apache Cassandra
  • Apache Kafka
  • Apache Hadoop (HDFS, HBase, Hive)

Spark and Kafka are popularly famous tools, and they provide an interactive environment. Go through these sites for more knowledge,

  • An introduction to Hadoop can be A Complete Guide to Mastering Hadoop (free).
  • The most comprehensive guide to Apache Spark for me is Spark: The Definitive Guide.

Other topics to study for becoming Big Data Engineer include Data Pipelines and Distributed Systems.

The skillset of Data Engineer

To initiate your career, you must study computer science as your major in university or college. Because this job requires a strong grip in mathematics, computer science, engineering, and other IT fields.

  • You need to have good programming skills (Python, Java, Perl, etc.)
  • Machine learning, have a basic concept in how to use data for statistical analysis and data modeling.
  • Extensive knowledge in Operating Systems (Linux, UNIX, and Solaris, etc.). As most of Big Data tools are based on these Operating Systems.
  • Enjoy solving complex problems. If you get frustrated, then this job is not for you, as it requires immense patience.
  • Communication and oral skills.
  • One must have very strong communication skills to deal with employees.
  • There are several complex projects, and Data Engineer must have strong leadership and project management skills.
  • Degree of computer science in bachelors and masters.
  • For improvement of performance and end-user experience, one must tune with Hadoop solutions.
  • Good grasp and knowledge of tools like MapReduce, Hadoop, and HBase, etc. 
  • Strong knowledge in SQL database.
  • Maintain, design, and construct data management systems.
  • Work together with data architects, modelers, and IT team members.
  • Integration of new data management technologies and tools of software engineering into current existing systems.
  • Build prototype, predictive models, and algorithms.
  • Install a disaster recovery system, also update it.
  • Developing data set for; data modeling, mining, and production.
  • Creation of customs software’s (specialized UDFs) and applications.
  • Induce several languages and tools.
  • Intense work on improvements in data efficiency, reliability, and quality.
  • International Data Management Association (DAMA)
  • The Data Warehousing Institute (TDWI)
  • Institute for Certified Computing Professionals (ICCP)

Responsibilities of Data Engineer

Organization to apply for Big Data Engineers


Big data are extremely huge datasets with massive volume.

A data engineer is someone who develops, maintain, and tests Big Data solution in an organization.

Few important things to know before starting a career as Big Data Engineer,

Algorithm and Data Structures

  • Learn SQL (Structured Query Language) 
  • Tools for Big Data

One must also go for Big Data certification and the best data science certification.


About The Author
Associate Instructor

Owais Rashidi

Owais is an associate instructor at QuickStart having prior experience of doing projects in .Net, SQL Server, SSIS, Data warehousing and Business Intelligence. He has done Bs in Enterprise Resource Planning (ERP) which is a unique blend of both Software Engineering and Business Administration. And is also configuration and implementation of SAP core modules.