Big Data Job Description 2024

In 2024, when data is valued and thought to have potential, like oil, companies in all fields will try to use its strength. Big Data engineers build and take care of the systems that collect, store, and analyze very large datasets. Thanks to technology and the exponential growth of data, big data engineers are now more important than ever. Their work supports business operations, promotes new ideas, and uses data to make smart decisions.

Big Data Engineer:

Engineers who work with “big data” receive, store, and analyze large amounts of data. They understand how to use tools for big data and build software. Data scientists look at data and usually have backgrounds in statistics or analysis. Big Data Engineers, on the other hand, build and run infrastructure for processing large amounts of data.

Big Data Engineer
Big Data Engineer

Big Data Job Description

Big Data Engineers help businesses handle their data and get value from it. There has never been a greater need for skilled professionals to handle, process, and analyze the huge amounts of data that businesses produce. Here’s a more in-depth look at the duties and parts that come with the Big Data job description.

Defining Data Retention Policies

Big Data engineers set the rules for how long data should be kept in the system’s memory. These rules find a balance between how much data is worth and how much it costs to store and follow the rules set by law and government.

Developing Hadoop Systems

Creating and maintaining Hadoop-based ecosystems is an important part of the job because they are needed to process big datasets. Setting up Hadoop clusters, taking care of the environment, and making sure the system works well and reliably are all part of this.

Analyzing Processed Data

Big Data Engineers look at datasets to find patterns, trends, and ideas after they have been processed. The results of this study are very important for business plans and making decisions.

Architecture Design

Creating a data architecture is a key part of storing, processing, and getting large amounts of data efficiently. Big Data Engineers make data architectures that are scalable, reliable, and efficient based on the needs of their company.

Conducting Research

In the area of Big Data, you need to keep looking into new technologies, tools, and methods to stay ahead. This study is very important for making data infrastructures and solutions better.

Data Cleaning and Preparation

Data needs to be cleaned up and set up before it can be examined. This means getting rid of mistakes, duplicates, and useless data to make sure the quality and dependability of the data.

Developing Data Pipelines

Data pipelines move data automatically from where it comes from to where it needs to go, so it can be analyzed and used. Big Data Engineers plan and set up these processes, making sure they work well and don’t make any mistakes.

Designing and Implementing Relational Databases

Relational databases are still very important for managing data, even though big data tools are getting a lot of attention. Big Data Engineers make these databases so that they can store, query, and handle data well.

Providing Data Access Tools

Another important job is to make sure that analysts, data scientists, and other interested parties can easily access and work with the data they need. This can be done by creating or integrating tools that make this possible.

Creation and Maintenance of Analytics Infrastructure

Building and maintaining the infrastructure for data analytics is what makes it possible to evaluate data well. This technology lets you do advanced analytics, use machine learning models, and process data in real time.

Developing DataSet Processes

Big Data Engineers come up with ways to create, change, and analyze large sets of data for specific research projects. This customized method makes it possible to analyze data more effectively and with more focus.

Gathering and Processing Raw Data

An important task is to get raw data from different sources and turn it into a form that can be analyzed. This handling makes the data usable and makes sure it is organized correctly.

Working on Data Architecture

The overall data architecture of a company is always being built up and improved. This architecture tells everyone in the company how to store, handle, and get to data.

Big Data Engineer Role

All of those things are part of the job, and the main focus is on managing and using big data to help the company succeed.

Conducting Performance Optimization

Making sure that the methods for processing and storing data work as efficiently as possible is very important. To do this, systems must be constantly checked, tuned, and updated to handle growing amounts of data and more complicated data structures.

Machine Learning

A lot of the time, Big Data Engineers work with machine learning models. They either give the models the data they need to learn or add the models to the data processing pipeline to make analytics and decision-making better.

Big Data Engineer Skills

Big Data Engineer Skills
Big Data Engineer Skills

Big Data engineers are on the cutting edge of technology because they handle and make sense of huge amounts of data. Below is a complete list of skills that a Big Data Engineer must have in order to do their job well:

  • To store, process, and analyze large datasets quickly, you need to know how to use Hadoop, Spark, Kafka, and other “big data” processing tools.
  • For building and handling big data pipelines and applications, you need to be very good at programming, especially in languages like Java, Scala, Python, and SQL.
  • For storing and managing data, it’s important to know how to use both traditional SQL databases (like MySQL and PostgreSQL) and NoSQL databases (like MongoDB and Cassandra).
  • To meet the needs of BI and analytics applications, you should be able to create data models and understand the basics of data warehousing.
  • Knowing how to use data flow and ETL (Extract, Transform, Load) tools, like Informatica, Apache NiFi, or Talend, to move and change data is important.
  • For analyzing data and coming up with ideas, it can be helpful to know how to use machine learning algorithms and analytics tools.
  • It’s helpful to know about cloud services like AWS, Google Cloud Platform, and Azure, since many businesses use them to store and process big data.
  • For setting up and maintaining data processing environments, it can be very helpful to know how Linux works and how to do basic system administration.
  • To protect and handle data responsibly, you need to know about data security principles, compliance regulations, and governance practices.
  • To handle the difficulties of handling big data sets and complicated systems, you need to be good at both analyzing and solving problems.
  • To turn data ideas into useful business strategies, you need to be able to communicate clearly with both technical and non-technical teams.
  • As big data technologies change quickly, it’s important to stay committed to ongoing education and keep up with the latest trends and tools in the field.
  • The ability to improve the performance of big data infrastructures and applications so that they can handle large amounts of data more quickly.
  • Learning how to use tools for data visualization is important for making data ideas easy to understand and share.
  • To lead big data initiatives, it’s helpful to be able to handle projects, which includes planning, executing, and working with people from different teams.

Salary of a Big Data Engineer

Here is a rough range of salaries for a big data engineer around the world:

  • In the United States, big data engineers can expect to make between $100,000 and $160,000 a year, though this can change based on experience, location, and business.
  • Canada: The price range is usually between CAD 70,000 and CAD 120,000 in Canada.
  • United Kingdom: In the UK, a big data engineer could make between £50,000 and £90,000.
  • France: In France, salaries can be anywhere from €60,000 to €100,000.
  • Australia: Big Data Engineers in Australia can expect to make between AUD 90,000 and AUD 150,000 a year.
  • Asia: In Asia, the range is usually between ₹500,000 and ₹2,000,000, but this depends a lot on the type of company and the person’s experience.

Companies Hiring Big Data Engineers

Giants in tech

  • Google: Google is known for its search engine, but it also has jobs in infrastructure development, data management, and research.
  • Amazon: To improve processes and the customer experience, Amazon hires Big Data Engineers to work on its huge e-commerce platform and cloud services (AWS).
  • Microsoft has jobs that focus on business data, cloud computing (Azure), and more.
  • Meta: Facebook (Meta) is hiring engineers to work on building a data platform for its social networks and virtual reality apps.
  • Apple hires Big Data Engineers to work on making products better, improving the user experience, and making operations run more smoothly.

Financial Services

  • JPMorgan Chase & Co.: Big data is used in banking and financial services to spot fraud, control risk, and learn more about customers.
  • Goldman Sachs uses “big data” to make better financial models, study the market, and help customers.


  • Philips has jobs that focus on using data analysis, predictive modeling, and patient care tools to make healthcare better.
  • Pfizer hires big data engineers to help find new drugs, analyze patient data, and make the company run more efficiently.

Retail and E-commerce

  • Walmart uses “big data” to improve its supply chain, study how customers behave, and make sales estimates.
  • eBay hires engineers to make auction systems better, make user experiences more personalized, and make operations run more smoothly.

Entertainment and Media

  • Netflix focuses on using big data to make content suggestions, improve the watching experience, and come up with ways to keep customers.
  • Spotify hires Big Data Engineers to look at how people listen to music and make personalized music suggestions.

Technology and Consulting Firms

  • IBM has jobs in AI development, data consulting, and cloud services.
  • Deloitte offers consulting services that include AI solutions, big data analytics, and plans for digital change.

Related Career Paths

People who are interested in Big Data Engineering and also want to work in technology or data science can take a number of related paths that lead to exciting job possibilities. Here are a few jobs that have something in common with the skills and goals of Big Data Engineering:

Related Career Paths
Related Career Paths

1. Data Scientist

Data scientists look into complicated digital data, like website user stats, and figure out what it all means so that businesses can make better decisions. They get useful information from data by using cutting-edge analytics tools like machine learning and prediction modeling.

2. Machine Learning Engineer

Machine Learning Engineers are in charge of putting machine learning apps into action. They make machines that can learn from data and decide what to do based on that data. You need to know a lot about both software engineering and data science for this job.

3. Data Analyst

Data analysts take big sets of data and process and analyze them statistically. They find ways that data can be used to answer questions and solve problems. Based on a deep understanding of statistical methods, they provide useful information through reports and visuals.

4. Cloud Engineer

Cloud engineers plan, set up, and take care of infrastructure and apps that run in the cloud. More and more, cloud services are being used to store and process data. Knowing how to use cloud platforms like AWS, Azure, and Google Cloud Platform is very useful.

5. Database Administrator (DBA)

Database administrators use special software to organize and manage different kinds of data, such as customer shipment information and financial data. They promise that only allowed users will be able to access this data and that it will be kept safe from people who aren’t supposed to be there.

6. Data Architect

Data architects plan, build, install, and oversee the data architecture of a business. They decide how to store, use, integrate, and manage data across different organizations and IT systems, making sure that data flows smoothly and safely.

7. Business Intelligence (BI) Developer

BI Developers come up with plans to help business users find the data they need to make smarter business choices. They make BI and analytics tools that turn data into information and run those tools.

8. Systems Engineer

Systems engineers keep an eye on all of an organization’s installed systems and equipment. They help make sure that systems and infrastructure are always available by being part in the whole process, from designing the system to maintaining it after it has been put into use.

9. Software Developer

Software developers work on making apps and the running systems that run them. For big data projects that need to make apps that process, analyze, and display data, knowing how to code is helpful.

10. Cybersecurity Analyst

Cybersecurity analysts keep hackers from getting into a company’s hardware, software, and networks. Their job is getting more and more important as the amount of data and complexity of cyberattacks rise.


Big Data engineers are very important for using the power of very large amounts of information to make decisions and come up with new ideas. Getting the right skills and information is important for people who want to start or move up in this exciting career path. The Post Graduate Program in Data Engineering by Simplilearn and Purdue is a great way to learn more about the basics of data engineering, big data technologies, and how they can be used in real life.


1. What is the job of big data?

Big Data is the process of gathering, processing, and analyzing very large and complicated datasets to find insights, trends, and patterns that can help businesses make choices, work more efficiently, and come up with new ideas.

2. What is the role of a big data engineer?

A big data engineer plans, builds, and takes care of the tools and systems needed to work with large amounts of data. They build data paths, take care of data storage, and make sure that systems can grow and work well.

3. Is big data difficult to learn?

It can be hard to learn big data because it is so complicated and you need to know a lot of different technologies and computer languages. But it is definitely possible if you work hard and have the right tools.

4. Is Big Data a good career?

Yes, working with big data is a great job. It’s in high demand in many fields, pays well, and is a key factor in making strategic business choices and new products.

5. What is the salary package for big data engineers?

Big Data engineers make between $100,000 and $160,000 a year in the United States, but the exact number depends on where they work and how much experience they have. Pay is changed to reflect local standards and the cost of living in other places.

About admin

Check Also

Data Science Consultant Jobs

The Exciting Landscape of Data Science Consultant Jobs

The field of data science has been one of the fastest-growing industries in recent years. …

Leave a Reply

Your email address will not be published. Required fields are marked *