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Big Data Engineer vs Artificial Intelligence Engineer



In the late 1900s, technology was considered “a nerd domain.” Things changed in the 21st century. Every day, hundreds of new artificial intelligence-powered apps and solutions are introduced online. Technology has created additional jobs due to the rapid adoption of artificial intelligence. Big data is also altering business structures. In the past, big data was viewed as meaningless information that took up too much server space. Thankfully, as technology developed and improved, businesses began to see the value of big data and use it to make better choices. Due to growing interest in big data and AI, two new jobs have emerged: big data engineer and AI engineer.

Artificial Intelligence vs. Big Data Engineering often needs clarification due to their similar skill sets. This article compares big data engineers to AI engineers to help you choose a career.

AI vs. Big Data

At this point, big data and AI (artificial intelligence) are here to stay. Data and AI are becoming synergistic, as AI is meaningless without data, and mastering data is impossible without AI.

Combining the two disciplines allows us to foresee business, technology, commerce, entertainment, and other trends. A Masters in AI degree proves to employers that you are trained and qualified to work in this evolving field.


Big Data vs. AI – Job Market

The data science market is forecast to reach USD 178 billion by 2025. AI is expected to increase by 13.7% to USD 202.57 billion by 2026. Both fields have grown in recent years, but which is better?

Data scientists and AI engineers are not programmers or mathematicians. Problem-solving differs among the fields. Data scientists employ analytical tools to gather data and draw conclusions. Artificial intelligence engineers utilize algorithms and software to uncover data trends.

Big data and AI differ in output. What’s best? Big Data or AI Engineer? Let’s review.

1.      Big Data Engineer vs AI Engineer – Roles and responsibilities

Big data engineering applies data science to real-world problems. Big data engineers create data pipelines. They constantly gather data from diverse sources for analysts and data scientists to process. Although the profile is not directly related to business teams or decision-making, it focuses on improving information flow and availability.


Big data engineers design, develop, build, install, test, and maintain data management and processing systems. They find and organize raw data for other professions. A big data engineer also gathers data from multiple sources. They collect, store, and process data. Other big data engineer duties include,

  • Create robust, scalable, and fault-tolerant data management systems.
  • To introduce innovative big data management tools and technology to keep ahead of the competition.
  • Try new data-collecting methods and use old data in new ways.
  • Combine several programming languages and tools to create a complete solution.
  • Use disaster recovery methods in case of mishaps.

Big data engineers must also be tech-savvy. They should understand big data technology and share suggestions with the team.

  • Knowledge of Java, data structuring, and big data basics
  • Cassandra, HIVE, CouchDB, and HBase experience
  • Knowhow on Analytics and OLAP

What else is there to know about the role of artificial intelligence engineers?

We now use artificial intelligence every day. An artificial intelligence engineer creates and integrates smart autonomous models into the software.

AI engineers use neural networks to build models for AI applications. These engineers developed AI-based systems for language translation, picture identification, and sentiment-based contextual advertising. They develop AI solutions with corporate stakeholders to improve operations, service delivery, and product creation.

Other duties include,

  • Create artificial intelligence and machine learning models, then turn them into APIs for other applications.
  • Explain the output to stakeholders.
  • Automate data science team infrastructure and AI product infrastructure.
  • Use statistical analysis to inform data decisions.

2. Big Data Engineer vs Artificial Intelligence Engineer – Primary goal

The work of a big data engineer is focused on discovering such patterns and trends. For this purpose, they seek out, clean, and process organized and unstructured data. Artificial intelligence engineers aim to give industrial models autonomy. An artificial intelligence engineer gathers much data and uses complex algorithms and iterative processing to make robots think like humans.

3.     Data Scientist vs Artificial Intelligence Engineer – Salary

Data scientists and AI engineers earn more depending on their abilities, experience, and company. Data scientists earn 812,855 lakhs, and artificial intelligence engineers earn 1,500,641 lakhs, according to PayScale. Depending on seniority, data scientists can earn 30 lakhs and artificial intelligence engineers 50 lakhs.


4.     Data Scientist vs Artificial Intelligence Engineer – Complimentary job roles

A big data engineer creates data products that aid in successful corporate decision-making. In contrast, an AI engineer aids organizations in developing unique solutions that promote autonomy. In contrast, an AI engineer makes a version of the model that you can deploy and add to the final product. AI engineers must also provide secure web service APIs for delivering models when necessary.

A big data engineer employs AI to address business challenges. In contrast, an AI engineer commercializes data science for external clients and internal stakeholders. Data scientists and AI engineers keep up with new technologies that could change how businesses interact with customers and how people do their jobs. However, a big data engineer has a more strategic perspective on the company than an AI developer. To create an AI solution that is effective and efficient when put into practice, both parties need to work together.

Final thoughts

Data scientists and AI specialists are in high global demand, making their field an attractive one in which to work. Engineers who work on artificial intelligence (AI) and data scientists work together closely, and both can open doors to promising career opportunities.


Checking your interests and preferences before deciding between these two professions is essential. Big data engineers are a unique breed with a deep love for data and managing big data. AI engineering is a good fit for you if you work well in groups and don’t like to keep your data in separate silos. Plan to power ahead in your career with Simplilearn online courses.

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