Home / Blog / Hiring Guide / How to Hire / Hire Big Data Engineer: Salaries, Stack and Roles

Hire Big Data Engineer: Salaries, Stack and Roles

Big Data is a collection of data that is large in volume but still growing exponentially over time. It is so large in size and complexity that no traditional data management tools can store or manage it effectively.

Although the Big Data concept itself is relatively new, the origins of huge data sets go back to the 1970s when the world of data was just getting started with the development of the relational database. Today, however, it is used all over the world in countless industries and sectors. 

While Big Data has come far, its use is still growing and being explored. Technologies that have expanded Big Data possibilities even further are cloud computing and graph databases. The cloud offers excellent scalability, while graph databases offer the ability to display incredible amounts of data in a way that makes analytics efficient and effective.

Who is Big Data Engineer?

Big Data requires a unique engineering approach. It’s because Big Data consists of tons of mixed, unstructured info that keeps increasing at high speeds. That’s why traditional transportation methods for data can’t efficiently manage the flow of Big Data. It requires developing new and innovative tools for sourcing, storing, and analyzing large amounts of unstructured data.

In recent years, leading enterprises in various sectors, including sales, research, and marketing, are actively accumulating and managing big sets of data. It is expected that by 2023, the Big Data industry will be worth around $77 billion. However, these industries are facing a shortage of the necessary expertise. As a result, Big Data software engineer experts are some of the most in-demand IT candidates.

Big Data Engineer vs Data Scientist

Some businesses may require data experts but may not be aware of the differences between the experts in the field. Let’s compare Big Data engineer vs data scientist:

The difference lies in their particular roles. Data Science involves extracting useful business insights from the data. Data Engineering involves designing the full process stack for collecting or creating, storing, and processing data in real-time.

Data engineers specialize in developing, constructing, testing, and maintaining architectures, such as databases and large-scale processing systems, while data scientists clean and organize data.

Data engineers with a Big Data engineer certification also deal with raw data containing human, machine, or instrument errors. This data is unformatted and can contain system-specific codes. These engineers must recommend and implement ways to improve the data’s reliability, efficiency, and quality.

On the other hand, data scientists get data that has passed the first round of cleaning. They use it to feed advanced analytics programs and machine learning and statistical methods to develop data for use in predictive modeling.

The Skills, Roles, and Responsibilities of a Big Data Engineer

The Big Data engineer roles and responsibilities are similar to that of a data engineer and can include the following: 

  • Designing and developing the architecture of Big Data platforms.
  • Managing and maintaining data pipelines.
  • Effectively customizing integration tools, databases, and analytical systems. 
  • Efficiently managing and structuring data sets. 

A Big Data engineer’s responsibilities include certain unique tasks in dealing with Big Data. Some of these include: 

  • Performance optimization

Performance becomes a major factor when dealing with Big Data platforms. Therefore, these engineers must monitor the complete process and apply the needed infrastructure changes to advance the query execution. 

  • Stream processing

Effectively setting up and maintaining streaming flows is one of Big Data engineers’ most important and most common roles today.

  • Deploying ML models

Big Data engineers are involved in the deployment process if a data scientist doesn’t have the skills to produce production-ready code and develop it in the pipeline. 

To perform these different tasks successfully, these engineers must have a certain set of skills. Some of the most important Big Data engineer skills include:

  • Databases

Databases are the core of data storage and organization. That is why it is so important to be familiar with their structures and language.

  • Cloud computing

Clouds are significant in storing and managing data sets since they present distributed access and better scalability than on-premises servers. Engineers must have excellent skills in working with cloud computing combined with Big Data engineer stack knowledge. 

  • Data warehousing 

Data warehouses store immense volumes of data for query and analysis. Most entry-level engineers are expected to be familiar with cloud services platforms and their ecosystem of data storage tools.

  • Algorithms and data structures

Big Data engineers focus mainly on data filtering and data optimization; however, a good knowledge of algorithms helps understand the big picture of the overall data function.

A data engineer’s skill set should also consist of a range of soft skills, including collaboration and communication. Data engineering is a very collaborative field, and engineers work with an extensive range of professionals.

To get a better picture of exactly what to look for in the ideal candidate, we should consider a Big Data engineer resume of a senior engineer: 

Resume of a Senior Big Data Engineer

Different Types of Data Engineers

Data engineers specialize in different fields. While the different areas of specialization may include the same educational background, these areas require very specific skills, knowledge, and experience. Some of the different types of data engineers include:

Azure data engineers 

An Azure data engineer specializes in data-related implementation duties, including ingesting data, provisioning data storage services, transforming data, implementing security elements, identifying performance bottlenecks, and accessing external data sources.

In search of talented Azure data engineer to empower your company performance? Count on Mobilunity! >>>

Google data engineers

A Google data engineer focuses on applying the principles of data engineering by using the Google Cloud Platform. This platform is highly secure and flexible, making it one of the most widely used platforms for businesses. 

Looking for dedicated Google data developer to boost your business? Rely on Mobilunity! >>>

Amazon data engineers 

An Amazon data engineer specializes in designing and building large-scale enterprise data solutions and applications using Amazon’s AWS data and analytics services. 

Hire with Mobilunity and get professional Amazon data engineer’s assistance with no waste of time! >>>

IBM certified data engineers 

An IBM-certified data engineer – Big Data designs and builds the right infrastructure needed for optimal extraction, transformation, and loading of data from many data sources using various cloud-based tools.

When sourcing a data engineer for a specific project, it is important to consider the unique requirements. This will determine what type of data engineer is needed. During the vetting process, specific Big Data engineer interview questions can be asked to determine a candidate’s specialty and level of experience and skills. 

Get help of professional vendor and hire dedicated IBM certified data engineer effortlessly! >>>

Different Programming Languages Used in Big Data

The different types of engineers specialize in using a variety of different programming languages. Let’s explore some of these: 


Software engineer Big Data experts work with Python engineers who use the language to develop cross-platform programming tools and software solutions, capable of processing big volumes and diverse data sets. 


JavaScript is a powerful client-side, dynamic language with a syntax based on both the Java and C languages. JavaScript engineers specialize in website programming, development, and implementation using a variety of data sets. 


Java is a high-level, object-oriented programming language designed to have few implementation dependencies. Java engineers can work with a Big Data developer to integrate Java into business applications, software, and websites. 


One tool that can facilitate statistical analysis and make data manipulation exponentially easier is R. R engineers work with Big Data software engineer experts to write code for data analysis, statistical computing, and modeling.


C++ is a cross-platform language used to create high-performance applications. It offers programmers a high level of control over system resources and memory. C/C++ engineers create software or mobile applications according to the functionality clients require. They work alongside data engineers to source the data required to identify these requirements. 


SQL is a structured query language mostly used in relational databases to query, manage and define data, as well as control access to it. Data engineers and SQL engineers work together to develop SQL databases and write applications to interface with SQL databases.


MATLAB is a multi-paradigm programming language. It allows the plotting of functions and data, implementation of algorithms, and creation of user interfaces. MATLAB engineers specialize in creating applications that can interface with programs written in other languages. 


Scala is a programming language that incorporates object-oriented and functional programming to create general software applications. Scala engineers work with data engineers to develop anything from large machine learning apps to basic web apps.


Cisco DevNet is Cisco’s program to help developers write applications and develop integrations with Cisco products and APIs. Cisco engineers work with Cisco Big Data engineer experts to develop data-driven applications that suit businesses’ unique needs. 

Big Data Engineer Salaries for Different Levels of Experience

One of the most important factors to consider when hiring a Big Data expert is the cost involved. Many things can influence the salary of candidates, including their level of experience. Let’s consider the entry level Big Data engineer salary, mid-level salary, and senior Big Data engineer salary in Ukraine:

Minimum Average Maximum
Junior Big Data Engineer$1,500*$1,900*$2,400*
Middle Big Data Engineer$2,500*$3,100*$4,500*
Senior Big Data Engineer$4,600*$5,300*$6,500*

*Ukrainian salaries are provided based on Mobilunity’s Recruitment Team research on the local job markets. All salaries are net and do not include the service fee (in the case of hiring on a dedicated team model). The salaries are provided for comparison purposes and could not be entirely accurate. Contact us to know the exact cost of hiring a developer corresponding to the required parameters.

Monthly Big Data Engineer Salaries in Different Countries

Another crucial factor that impacts salary rates significantly is the location. It’s one of the primary reasons why businesses hire Big Data engineers in different countries. Let’s look at the below table which includes the Big Data engineer salary for five countries:

  • USA: $7,486
  • UK: $4,637
  • Germany: $5,908
  • Switzerland: $10,362
  • Ukraine: $3,100*

*Ukrainian salaries are provided based on Mobilunity’s Recruitment Team research on the local job markets. All salaries are net and do not include the service fee (in the case of hiring on a dedicated team model). The salaries are provided for comparison purposes and could not be entirely accurate. Contact us to know the exact cost of hiring a developer corresponding to the required parameters.

From the above data, it is clear that the average Big Data engineer salary differs a lot from country to country. This is a major reason why companies outsource work, especially to affordable countries such as Ukraine. 

Discover more about:

Find Experienced Big Data Engineer with Mobilunity

Mobilunity is a well-established and highly recognized outstaffing company in Ukraine. We have more than 10 years of experience offering outstaffing services, including building Big Data Hadoop developer teams for businesses of all sizes in a large variety of industries. 

Our experts at Mobilunity hire Big Data engineering teams fast and use time-tested methods to recruit the best-matching candidates for clients. We have many satisfied clients all over the world, including CamptoCamp (Switzerland), Paidy (Japan), ZenChef (France), 3e Joueur (Canada), and DNest (Spain).

At Mobilunity, we aim to expand the operations of businesses worldwide. To achieve this, we follow the simple but effective process below: 

  • We pick top candidates that suit your ideal candidate profile.
  • We ensure our workers are set up with the right tools and resources for maximum productivity. 
  • We ensure contractual obligations are met and that clients’ needs are satisfied throughout the process.

If you want to hire a Big Data software engineer, contact the Mobilunity team. Get professional help effortlessly! 

All salaries and prices mentioned within the article are approximate NET numbers based on the research done by our in-house Recruitment Team. Please use these numbers as a guide for comparison purposes only and feel free to use the contact form to inquire on the specific cost of the talent according to your vacancy requirements and chosen model of engagement.

Contact us
Go Up
Exit the AMP-version