The method used to extract insights from big data includes associations, hidden patterns, market trends, and customer preferences. In order to understand customers and make profitable decisions, it is used in various industries, including healthcare, banking, education, and retail.
The big data market is anticipated to grow to $450 billion over the next three years, providing big data specialists with numerous job and career opportunities. With an average yearly salary of $116,145, big data engineering is one of the highest-paying technology jobs in the United States, according to Glassdoor. This guide will offer a road map to help you reach your goal of becoming a big data engineer if the industry's potential inspires you to do so.
What Does an Engineer in Big Data Do All Day?
Big data engineers oversee and maintain an organization's data infrastructure. They are in charge of planning, creating, analyzing, testing, and maintaining a company's big data sets.
How to Become an Engineer in Big Data?
1. Get the appropriate education first.
Obtain a degree in a related field, such as physics, math, computer science, software engineering, or math. The right educational background will give you the necessary technical and interpersonal skills for the position.
2. Acquire the Required Technical Skills and Hands-On Experience
To become a big data engineer, you must develop expertise and in-depth technical knowledge. You can improve your knowledge and get ready for the job by doing an internship, freelancing, or working in a similar position.
3. Develop Projects Using Actual Data
Projects give you a chance to present your work and demonstrate your data expertise. If you're unsure where to start, you can use data available to the general public like Kaggle or enroll in an online data science course in Pune.
4. Establish Contact With Others in the Sector
Developing your professional network is a great way to advance your knowledge. You can exchange projects, get feedback and advice, answer questions, find out about job openings, and get recommendations.
5. Ask for mentoring from experts.
Look for a mentor who can offer advice and assist you in developing your subject-matter knowledge and expertise. Connect with a big data specialist who can provide you with insightful advice. Take advantage of the opportunity to connect with experts by taking an online course.
6. Recruit for Entry Level Positions
A long-term career option is big data engineering, which is typically a senior . In order to expand your experience and profile, apply for entry-level positions in a related industry.
Is a Career as a Big Data Engineer Good?
Big data engineering offers a rewarding career path. According to the US Bureau of Labor Statistics, big data engineering falls under computer and information scientists, mathematicians, and statisticians, with projected job growth of 21% and 31%. In addition, according to Glassdoor, a big data engineer in the US makes an average yearly salary of $116,145.
The role and responsibilities of a big data engineer
* Creating and keeping up with software systems
* Preserving, evaluating, and enhancing data pipelines
* Keeping data in the repository for data
* Executing ETL procedures
* Data gathering and processing Construction of data architectures
* Participating in joint projects with other teams
Skills for Big Data Engineers
A big data engineer needs to be highly skilled across a wide range of specialties.
The top skills for big data engineers are listed below:
Like most technologically oriented job roles, programming is the most important skill for a Big Data Engineer. A Big Data Engineer must have practical experience with any popular programming language, including Python, C++, and Java.
2. Database and SQL:
In-depth DBMS and SQL knowledge comes next, after programming. This will make understanding how data is managed and maintained in a database easier. For any Relational Database Management system, you must be able to write SQL queries.MySQL, Oracle Database, and Microsoft SQL Server are some of the popular database management systems for Big Data engineering.
3. Data warehousing and ETL:
As was already mentioned, performing ETL operations is one of a big data engineer's main duties. You need to be knowledgeable about building and using a data warehouse.
4. Domain Knowledge:
Having industry knowledge is another skill required to succeed as a big data engineer. This will help engineers understand the problem and solve industry problems using cutting big data tools. With an IBM-accredited data science and data analytics course in Pune, you can acquire the domain-specialized training and stay ahead of others.