9 Skills and Competencies to become a Big Data Developer

If you’re interested in assisting organizations with technical infrastructure issues, a career as a Big Data developer is a great option. Big data is particularly prominent in this era. Technological advancements have left companies grappling with tons of data generated every second.

Hence, professionals who can control and utilize this massive amount of data are in high demand. This guide will help you understand what it’s all about and how to become a big data developer.

What is Big Data?

Big data refers to the extensive data businesses have to deal with daily. Such data may be structured or unstructured.

The data can be used for strategic business moves.

The greater volumes of data in this era make it significantly different from what businesses had to contend with in the past. Hence, it came to be known as big data in the early 2000s.

These characteristics give a more precise definition of what big data is:

Volume – Huge volumes characterize big data, made up of information from multiple sources including social media, business transactions, and sensor or machine-to-machine data. This data requires new technologies like Hadoop to store and utilize.

Velocity – Big data streams are far greater than the past, which necessitates advanced methods for real-time management. The data comes from sensors, RFID tags, and smart metering, among others.

Variety – The complexity of dealing with big data is further compounded by the multiple formats businesses have to deal with, including structured and numeric data within traditional databases; as well as unstructured email, text documents, video, stock ticker data, audio, and financial transactions.

Variability – Inconsistencies in data streams are a further challenge. This necessitates having the capacity to deal with periodic peaks like trending topics in social media.

Opportunities Available for Big Data Developer

As much as big data is challenging to manage, it offers excellent opportunities for businesses.

Through the analysis of big data, organizations can gain a deep understanding of their clients. This helps in developing better business strategies and effectively allocating resources for smarter operations.
One place where big data plays a crucial role is in understanding cyber-security threats. Big data analytics provides better detection mechanisms of vulnerabilities.

Big data plays a crucial role in redefining how industries operate. It provides data-driven direction on how companies should best serve clients. This makes big data a vital asset for the leadership of any organization.

Governments benefit from big data too. Monitoring data streams can help in smart city planning as well as building sustainable water, electricity, and transportation systems. This, in turn, impacts budget planning processes.

Who is a Big Data Developer?

With the increasing need for big data management, big data developers have become a critical asset for organizations.

Big data developers cater to specific big data needs of organizations. Their role is to solve big data requirements and problems.

The work of big data developers involves creating, testing, implementing and monitoring big data applications that meet the company’s strategic goals. Such professionals are in high demand across different industries ranging from healthcare to financial companies.

A day in the life of a big data developer would typically involve such responsibilities as:

  • Writing code for key business components
  • Conducting technical training sessions
  • Mentoring and serving as a resource for junior personnel
  • Overseeing technical aspects of development projects
  • Serving as team leaders for specific projects
  • Explaining business segment services to executives

How to become a Big Data Developer?

Today, becoming a Big Data Developer has become easier than ever. You can find various online big data certification training courses that can help you learn Big Data and even get certified in it. Apart from that, to succeed as a Big Data Developer, you need a foundational interest in assisting organizations with technical infrastructure issues. That also means having a problem-solving aptitude.

If you want to take it upon yourself to learn big data without any help, you can then on that fundamental passion for technical infrastructure, by developing a range of specific skills and competencies that a big data developer must have, including:

1. Data Visualization

The quantity and diversity of data generated in business environments necessitate the use of such data visualization tools as d3.js, Tableau, and others.

With data visualization, people can better understand unstructured and semi-structured data. This way, you can derive critical insights by revealing hidden details that help in business growth.

2. Machine Learning

Computational processing of big data in growing volumes and varieties through machine learning is cheaper and more powerful.

With knowledge of machine learning, you can rapidly and automatically derive models to analyze complex data. This is essential to delivering faster, large scale, and accurate results. Such precise models help organizations better identify profitable opportunities.

3. Data Mining

Data mining is a necessary skill for a Big Data Developer.

Data mining helps you maneuver unstructured data and derive insights. You’ll be sifting through unnecessary and repetitive information to determine relevant details. Then, you can use it to assess and predict outcomes.

4. Statistical Analysis

Big data is all about statistics.

Therefore, as a big data developer, you must be good at quantitative reasoning. That means having a background in statistics and mathematics. To achieve this, you can learn statistical tools like SAS, R, Matlab, Stata, or SPSS.

5. SQL and NoSQL

Working with Big Data inevitably involves working with databases.

Hence, big data developers must have the necessary knowledge of database query languages. You should know both SQL and NoSQL. The simplicity of SQL makes it useful in many big data challenges today, despite it not being used to solve all cases. Distributed, NoSQL databases such as Cassandra and MongoDB are taking over the Big Data jobs previously handled by SQL databases. That means you must also have the ability to use and implement NoSQL databases.

6. General Purpose Programming

Big Data Developers must code to conduct a statistical and numerical analysis of massive data sets.

So, you should learn to program in such languages as Java, Python, C++, Scala, and others. Knowing one language well will help in grasping the rest.

7. Apache Hadoop

Hadoop is indispensable for Big Data.

You have to master Hadoop to succeed as a Big Data Developer. Get in-depth knowledge and experience of Hadoop core components and related technologies like HDFS, Flume, MapReduce, Oozie, Pig, Hive, YARN, and HBase. Professionals with such competencies are in high demand.

8. Apache Spark

Spark is another critical technology for big data processing.

This open-source data processing framework is developed around ease of use, speed, and sophisticated analytics. It serves as an alternative to Hadoop MapReduce. It provides enhanced functionality by running on top of existing HDFS infrastructure. And it supports the deployment of Spark applications in existing Hadoop v1 clusters, Hadoop v2 YARN clusters or Apache Mesos.

9. Understanding Business

Since the main motive of big data analysis and processing is using the information for business growth, you must have a general understanding of business.

With domain expertise, Big Data Developers can better identify relevant opportunities and threats. This also helps in designing practical solutions and communicating the issues with different stakeholders.


To gain all those necessary skills of a big data developer, you cannot do without an in-depth training course.

You need training that’s up-to-date with the current trends and best practices in the industry, especially since it continually evolves to meet new challenges. Such training should also be comprehensive enough to cater to multiple competencies needed when working in different industries and organizations.