Earn the Most-coveted Senior Big Data Engineering Certification
Data engineering stays at the frontline of the data strategy in an organization. It helps to find creative and insightful solutions for the organization’s data. It deals with the application of science and technology, handles data problems, and processes bottlenecks.
The demand for data engineers has grown by 38% in the last year- 2019 and this marks just the beginning! The highest paying cities in the United States for data engineers as per Indeed.com includes New York ($152,010), San Jose, CA ($145,218), Boston, MA ($142,328), Seattle, WA ($138,346), Chicago, IL ($126,482), Plano, TX ($124,233), Austin, TX ($122,809), and Atlanta, GA ($120,146).
The average salaries for certified big data engineers are as high as you can see here.
. Big Data Engineer salary in the United States earns $158,000 Source: Salary.com
.The average salary for a Big Data Engineer is $89,838. Source: PayScale
.A data engineer earns $127,800 per year in the United States with a $5,000 cash bonus Source: Indeed.com
With data engineering, you can make data work for you. If developing information processes for data — acquisition, transformation, migration, verification, modeling, and mining is your forte, then you should become a data engineer by earning a relevant data science certification.
Being a big data engineer, you can –
· Create, optimize, and monitor data infrastructure using the right tools
· Setup data pipelines for ETL and further business processes
· Establish production-ready & real-time data Infrastructure
· Learn Hadoop development and its implementation
· Design, build and support Hadoop applications
· Make a logical, conceptual, and physical design for large volumes and diverse data
· Develop code for data injection and analysis as well
To learn big data, one of the most popular industry-recognized certifications for Big Data Engineers is Senior Big Data Engineer Certification (SBDE). Catch up the data science trend by earning this most beneficial Certification.
Here is a brief note about all you should know about this certification.
All you need to know about SBDE certification program
The SBDE credential provided by the Data Science Council of America (DASCA) is the most credible third-party, vendor-neutral certification known across the globe.
To gain certification, there are FOUR convenient tracks for software engineers, coders, and programmers from diverse backgrounds and experiences. The candidates should have completed a Bachelor’s or Master’s Degree in Computer Science, Technology, Engineering, Applied Sciences, or related disciplines.
Additionally, the aspiring candidates must possess a minimum of 2 years’ experience (1 year for Master Degree holders) in using Python, Java, or any other programming language.
Further, as you get registered for the SBDE certification program upon fulfilling the eligibility criteria, you will get The DASCA Official Exam Preparation Kit published by Wiley. It consists of 2 textbooks in essentials of Big Data programming, Lab workbook, e-lab facilities for practice, online learning, and preparation resources.
You can also visit the website www.dasca.org to understand the specifics on learning coverage, structure, registration process, renewal of Big Data Engineering certification, and other details.
Here is a quick exam fact about the SBDE certification:
· Mode of Exam Delivery: Online
· Proctoring: Web-proctored
· Prerequisites: Computer with good Internet speed and ExamStrongTM verified environment
· Duration: 100 minutes
· No. of Questions: 85 MCQs
· Passing score: 65% correct answers
As you clear your exam, you will also get awarded with the SBDE Digital Badge, which adds credibility to your online professional presence. You can showcase the credential on web pages, social media platforms, and email signatures. Also, you can allow your prospective employers, recruiters, and colleagues to validate your credential.
Build your future in a data science career by earning this most-coveted SBDE Certification. Be a notable professional in the big data industry.
