How to become a big data engineer?

The Big Data engineer is the in-demand field that creates tremendous job opportunities for freshers who have satisfying hands-on exposure along with industry-accredited certificate.

As Data is being considered like oil for businesses and big data technology becomes a must-skill for freshers to perform any IT operations.

This is such a golden period for freshers and experienced candidates to begin their career in big data along with the in-depth knowledge of tools like Hadoop, Spark, and so on.

It gives a promising future with rapid and exponential career growth through continuous learning on the updates of big data technologies.

Top companies are employing skilled freshers for performing big data processing through various profiles with different responsibilities.

Gain expertise in industry-specific skills for grabbing the opportunities to work in a big data platform.

Big Data Certification adds value to your profiles and makes you stand from the queue with unique knowledge.

The average salary of entry-level big data professionals ranges between 4 to 7 LPA and it varies according to the size and location of the employer.

Applications of Big Data Processing

Big Data Processing is implemented in the following industries that generate numerous opportunities for freshers with hands-on exposure.

  • Banking and Securities are using big data processing to manage financial market activities
  • Communications, Media, and Entertainment is using big data for creating contents, recommending desires, and measure content performance
  • Healthcare providers are using for retrieving health-related insight from raw data
  • Education sector is using big data engineer for deploying learning management systems as per trending industry requirements.
  • Manufacturing and Natural resources are using big data for various purposes like tools optimization, forecasting demands, integrated business planning, risk analysis, and shipping tracking, and so on.
  • Government sector is using big data for fraud detection, financial market analysis, health-related research, and environmental protections.

Prerequisites for learning Big Data

The learning of big data is easy and it does not require any hard prerequisites for freshers.

Basic knowledge in the following factors helps the freshers to learn big data with respective tools and kick-start their career in this futuristic field.

  • Programming Skills: Python, Java, or R as it helps to understand analytics.
  • Database Knowledge: SQL, RDBMS, and MongoDB for understanding existing data structures.
  • Linux: For understanding deployments of tools like Hadoop.
  • Business Knowledge: For understanding the project requirements.
  • Statistics: For understanding analytical-related concepts.
  • Passion and patience for learning in-depth concepts.

If you are interested but don’t have knowledge in any of the above-mentioned areas, need not worry as most of the Big Data Training Institutes are providing courses from scratch with satisfied hands-on practices.

In-demand Big Data Tools You Need to Know

Gain expertise in big data tools with certification help the freshers to obtain the jobs easily.

Following are the popular big data tools used widely in giant companies around the world.

  • Hadoop: It is an open-source framework and big data is incomplete without it. It offers massive storage for any kind of data with tremendous processing power and the capability to handle multiple tasks at a time. It is worth learning about Hadoop processing and it surely adds value to your profile in the recruitment race of top companies.
  • MongoDB: It is the best for datasets processing and it provides storage for mobile apps, product catalogs, content management systems, and so on. Learning MongoDB requires some basic knowledge of queries to operate easily.
  • Cassandra: It is widely used by giant companies like Cisco, Twitter, and Netflix as it is developed by Facebook for NoSQL solution. It provides high-performance and is implemented to handle the massive amount of data used for commodity servers as it is a distributed database. We do not worry about hardware failures as it more reliable in data management.
  • Talend: It is a real-time big data platform and supports technologies like machine learning, IoT, web designing, email, and smartphones. It is used to handle multiple data sources and accelerates every move of the database. It offers numerous connectors and enables the user to customize solutions as per requirements.
  • Storm: It is useful for real-time processing of structured and unstructured datasets. Apache Storm is a tool with special features like reliability, fault-proof, and compatibility for all programming languages. It is a product from Apache as an open-source framework with a distributed computing environment.

Apart from these, there are some more big data tools such as Oozie, HCatalog, Elastisearch, Drill, Qubole, Rapidminer, Apache SAMOA, HPCC, Lumify, Datawrapper, Knime, and Xplenty, etc.

Learning of these big data tools has pros and cons that should be chosen as per the requirements and usage.

Career Scope of Big Data for freshers

big data engineer is a huge field that brings tremendous job opportunities for freshers to perform the following roles and responsibilities:

  • Big Data Developer: They develop code used for data analysis and custom applications.
  • They have to explain designing concepts to clients or stakeholders and develop ETL and ELT process to discover the right data and make them in an understandable format. Big data developers should understand data structures, data sources, and relationships among them. They must have strong analytical and logical skills for implementing their responsibilities wisely.
  • Big Data Administrator: They build, setup, and configure clusters along with the knowledge in big data tool installation and configuration. They have to manage the health of clusters by providing and managing user access. Big Data Admin should help the developer for developing and implementing online system security. They have to work fluently with Big Data Architects for designing and setting up the storage and database structures.
  • Big Data Architect: They are responsible for conceptualizing, planning, and designing big data systems with required tools. They have to design functional and technical architectures along with proper knowledge and understanding of ecosystem technologies and applications. They should analyze the system and technical requirements for managing databases. They will work closely with big data admin and developer for deploying and managing big data solutions with complete knowledge in the lifecycle of big data solutions.
  • Big Data Analyst: They should analyze data and make it contextualize for business needs and functions with a strong understanding of data and business operations. Big Data Analysts should be skilled in ad-hoc data analytics for working with IT and business operations.
  • Data Visualization Developer: They should know any data visualization tools like Tableau, PowerBI, and QlikView for developing data visualization that helps decision-makers and value-added analysts. They should have a strong understanding of data structures and data flows to ensure the right data for expected results through reporting and analytics. They should work closely with data quality analysts for ensuring data completeness and integrity.
  • Big Data Scientist: They are responsible for predicting analytics modeling and development and analyze complicated data to help decision-makers. They should be skilled and experienced in software engineering and strong knowledge of mathematics and statistics.
  • Big Data Steward: It is one of the important roles of the Big Data platform that enable the organization to spend less time finding the right data and more time adding value to data. They assist all the roles, processes, and technologies of an organization to implement data quality and promote analytic cultures. They will take care of defining policies, regulations, and auditing of data and work closely with the IT department and business functions for sharing trending mechanisms.

Learn Big Data processing to perform any role mentioned above with the right skills. Enhance your fundamental database skills to compete with the big data world through certification and training provided by specialized Big Data Training Centers.

Significant Big Data Skills

Any company can conquer in business completion using big data processing and it requires certified professionals who have the following sought-after skills:

  • Analytical Skills for understanding complex data and solve problems along with mathematical and statistical knowledge.
  • Data Visualization Skills to convey the proper message to the management and decision-makers.
  • Strong knowledge in the business domain and big data tools for retrieving useful insights from raw datasets.
  • Programming Skills for understanding the pattern of applications. Expertise in programming languages like Scala, Java, Python, or R is an added advantage for big data professionals.
  • Problem-Solving Skills for solving real-time problems with creative solutions using big data tools and technologies.
  • SQL knowledge for understanding the traditional data models and methods.
  • Data Mining Skills using an application like Knime, Mahout, Rapid Miner, etc.
  • Familiar with trending technologies such as Matlab, R, SAS, Scala, SPSS, and Hadoop help them survive in Big Data Field.
  • Familiar in Public and Hybrid Clouds for storing and retrieving data virtually throughout the world. Understanding AWS, Azure, and Alibaba cloud services help them work in the big data field efficiently with productivity.
  • Non-Technical skills like Communication Skills, Interpersonal Skills, and Aptitude Skills help them to grab opportunities from giant companies like Accenture, IBM, Deloitte, and Google.


The learning of Big Data makes way for grabbing numerous opportunities worldwide and it brings assured job if you enhance your fundamental skills as per the industry requirements.

Freshers can learn from scratch through any Big Data Institute and equip you for performing various responsibilities.

Big Data Processing is easy to learn and implement through hands-on exposure and regular practices.

Get the Best course and shine in the big data field for reaching your career goals.

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