Top Big Data Developer Skills You Need to Master in 2023

Big data is gaining a lot of attention over the last couple of decades. It seems to become massive in the IT world and will continue to do so for many years to come. Big data refers to the large pieces of data, structured and unstructured that flood global organizations every day. Even though the amount of data is huge, that’s not what’s important, but what businesses do with it, or how they use it. It can not only be only used to get customers’ insights but also helps in strategizing for the future. Since it is becoming quite popular, therefore businesses are finding the need to hire big data developers for smooth operations. In this blog, I will discuss some of the most essential skills that big data developers should have and become an asset for your company:


Yes, programming is one of the most important skills that big data developers should have. Even though they don’t need to have years of experience with programming, they should at least know some basic coding and are comfortable doing it. Big data is still strengthening and therefore there are no proper processes to deal with complicated and unstructured data. Speaking of, you should know the following languages: R, Python, Java, Ruby, C++, Julia, Scala, because the unknown can become challenging for you to become a big data analyst. 

Data warehousing 

It’s a process of managing and collecting data from different sources for providing meaningful marketing insights. Therefore, it is one of the top skills that big data analysts must need. 

Soft skills

Every other developer needs to have soft skills because nothing works without collaboration. And when you are collaborating in a team, soft skills become essential, because you don’t want the other person you are coordinating with to think you are being rude only because you don’t know how to handle the situation. Therefore, you should understand how to talk to your team members and have soft skills such as critical thinking, teamwork, problem-solving, work ethic, how to talk to each other in a team setting, and career management. 

Analytical skills 

Then there come the analytical skills – it is also one of the most important expertise required to be an expert in your domain. Employers need their employees to find solutions to problems efficiently. This is where analytical skills come into play. Analytical skills help to solve critical problems. Through these skills, employees can detect patterns, brainstorm, observe and make quick decisions. For a better understanding of complicated processes and for efficient and immediate resolution of problems, analytical skills are very important for big data experts. 

Computational framework 

A big data developer should have knowledge of computational frameworks like Apache spark, storm, same, and flink. Also, the Hadoop computational framework is very important to understand. Speaking of, have you ever wondered how Google or Facebook can deal with such large quantities of data and user information – all the data is coming from social platforms, devices, etc. therefore, Hadoop is a framework as mentioned above that enables the processing of large chunks of data through simple programming. It scales up the data from one service to hundreds of machines for local storage and computation. Additionally. The library handles and detects failures if any at the layer, therefore, it is considered as a high availability service. 

Business knowledge 

To evaluate and validate the data, the big data developer must have all the information about the industry. They shouldn’t just have the primary knowledge, instead, they should be considered experts on their domains and we are only talking about people with years of experience. Of course, newbies would take a lot of time to learn about and know the business and the industry they are working in. They should understand the technical and business aspects of their industry. 

Know-how of the big data tools 

Well, this one is a given, if you are looking to hire big data developers then they should have the knowledge of at least some of the following big data tools to get started:

Cloudera Distribution for Hadoop

This tool is basically for enterprise-level corporations. It is completely open-source and free. It encompasses Apache Hadoop, Apache Spark, Apache Impala, etc. in addition, it is very easy to implement; it has easy administration, including top security and governance. 

  • Apache Cassandra: Then we have Apache Cassandra. Just like CDH, it is also free and open-source. it is built to manage large chunks of data spread across several servers. It is highly available. Some pros of Apache Cassandra are: as mentioned above it handles huge chunks of data efficiently, it has a simple ring architecture and it has log-structured storage.
  • Data wrapper: next up is the data wrapper. It is also an open-source platform specifically for data visualization and can help create intuitive charts and graphs rather quickly. Some famous names like the Times, Fortune, Bloomberg, Twitter, etc. use data wrapper.
  • MongoDB: it is NoSQL, and a document-oriented database written in C, C++, and JavaScript. It is an open-source, free-to-use tool and supports multiple operating systems such as window vista and Linux. It is easy to learn. It provides support to multiple platforms; it is easy to maintain and is also very reliable and low cost.

How to hire big data developers?

  • If you are looking to work on big data projects and do not know how to hire big data developers, then we are here to help. Finding big data developers can be huge and very daunting especially when you are looking for permanent developers. Hiring permanent and in-house developers takes time and effort and not even thinking about the costs. In-house hiring comes with its own list of disadvantages whereas outsourcing or staff augmentation are some of the best ways moving forward because they offer a time and cost-efficient solution.
  • You can outsource your big data development projects to the outsourced company and meanwhile focus on core business operations to make sure everything and everyone agrees.
  • We mostly specialized outsourcing results in higher efficiency since outsourced companies in their domain because they have been working on similar projects for clients all around the world, so they are very well versed with the ins and outs of every kind of technology including big data. They can offer the best solutions.
  • Hiring and recruiting employees to take time. But when you outsource our operations, you don’t need to hire employees or hire big data developers in-house. Meaning no extra recruitment costs.
  • You get to expand your talent hunt with access to talent from all across the world.
  • Outsourced companies are not just companies that you have outsourced, instead, they are your partners. The best part is they take complete ownership of the project from the initial stages till the implementation and some even after that. Meaning no need to spend hefty amounts of money on maintenance when you are getting everything in a highly cost-effective outsourcing package. The reason outsourcing is the best way forward if you are looking to hire big data developers for your next extensive project.

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