Here is Everything You Need to Know About Big Data Developer

Here is Everything You Need to Know About Big Data Developer
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The data-driven world is in dire need of big data developers

Big Data Developer

Average salary (Per annum): US$87,321

Roles and Responsibilities: Big data developers are responsible for the actual coding or programming of Hadoop applications: quite similar to a Software Developer. They could work on trillions of bytes of data each day with the help of different programming languages like Java, C++, Ruby, etc. along with several databases.

Qualifications:

  • Knowledge of big data frameworks or Hadoop-based technologies.
  • Knowledge of real-time processing framework (Apache Spark).
  • Knowledge of SQL based technologies.
  • Knowledge of NoSQL based technologies like MongoDB, Cassandra, HBase.
  • Knowledge of any of the one programming language (Java/Python/R).
  • Knowledge of visualization tools like Tableau, QlikView, QlikSense.

Top Online Courses:

Big Data Developer by Simplilearn: Enter the world of big data engineering with this certification course. It features masterclasses and asks me anything sessions by IBM experts. Learn job critical skills like Big Data & Hadoop frameworks, leverage the functionality of AWS services, and learn to use the database management tool and MongoDB to store data via interactive live sessions, practical labs, & industry projects.

Data developer Learning Path by Coursera: If you are looking for guidance and knowledge to begin your career as a data developer then this path is one of the best options available online. No experience is required to begin your learning and you can follow a step-by-step plan based on the relevant recommendations provided to you. Making use of the lectures and hands-on projects to work on your skills and by the end of the path, you will be ready to apply to your dream job.

Become a Big Data Developer: Mastering the Concepts LinkedIn Learning: In this learning path, you will explore all the essential concepts that will equip with you the skills required to implement them in real-world situations and pursue a career in this field. Begin with the foundational training that will acquaint you with the necessary technical jargon and concepts before moving on to databases that can be used to store and manage any scale of data.

Top Institutes Offering this Program:

  • Master's in Data Analytics: Pepperdine University
  • M.Sc. in Data Engineering: Jacob University, Germany
  • Masters of Science and Big Data for Value: Escca School of Management, Paris

Top 5 Recruiters

Deloitte: Deloitte is a leading provider of audit and assurance, consultancy, financial advisory, and tax services, etc. This information is stored in the form of data and so data engineers are needed for the company for maintaining the organization's whole data ecosystem, this includes data sources and databases to data storage solutions.

Capgemini: Capgemini is a consulting, technology services, and digital transformation company with data used for defining the end of the database, and then formulates the organizational data strategy, including standards of data quality, the flow of data within the organization, and security of the data.

Fractal Analytics: It has emerged as one of the top analytics service providers in the country.  The company has a global footprint boasting of several Fortune 500 companies from industries like retail, insurance, and technology. It has many branches in all parts of India hiring new positions.

Amazon: It is one of the biggest e-commerce companies around the world and is also among the top data recruiters worldwide. Amazon is a giant of data and to comprehend the intensity of data it requires Bigdata developers for its core operations from marketing streamlining, logistics, and inventory management to sales expectation and even HR analytics.

Bank of America: It is an American multinational bank that relies on huge amounts of data architects for building complex computer database systems that are accessible, useful, and secure the processes of the bank and its data by understanding the business need and exploring the existing data structure.

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