Who is a Big Data Developer?
Big Data is a number of big data generated by using data every day. This data can come from various sources such as social media posts, sensors, online videos, digital images, online purchase transaction records, mobile phones, traffic on various websites, email messages and so on.
Big Data Developers are responsible for coding or programming Hadoop applications which are actually very similar to Software Developers . They can work on trillions of bytes of data every day with the help of various programming languages such as Java, C++, Ruby, etc. Together with several databases.
Unlike a data scientist, a Big Data Engineer is less likely to deal with statistical methods and Machine Learning .
Examples of several companies using big data are:
- Netflix: Netflix has focused on being able to get or predict what its subscribers will actually enjoy. With that in mind, Big Data is the fuel that powers the ‘recommendation engine’ designed to serve this purpose.
- Walmart: Walmart’s big data solutions were developed with the goal of redesigning global websites and building innovative applications to customize the shopping experience for customers while increasing logistics efficiency.
- Uber: Uber’s biggest use of data is price spikes
Jobs and Responsibilities of a Big Data Engineer are:
- Develop and maintain a data network that implements the ETL process
- Design, build, install, configure and support Software
- High-speed queries.
- Maintain data security and privacy
- Propose design changes and suggestions for processes and products
- Manage and implement HBase.
- Perform extensive data storage analysis and discover insights.
- Work on different data sets.
- Build scalable, high-performance web services for data tracking.
The salary of a Big Data for newer Normally starts from 5 million depending on various factors such as the company, position, location, and most importantly your interview performance and the position where you are hired, etc.
Everyday Workload Vitali Dedkov, Lead BI Analyst/Data Engineer from Russia wrote in quora answer
“It varies, but for me a lot of time is spent working with our fellow Data Scientists group and our business group and trying to understand exactly what needs to be done and how to do it in a way that we can deliver results. quickly and cost-effectively.
This means that I spend my day working on data processing, testing result sets, and then reviewing them with end users.
On top of that, it also updates the documentation to ensure that if I want to see what I did months ago, I’ll be able to find something I wrote.
Once that’s all done, keep an eye on the latest news coming out of Azure/GCP/AWS on Data Engineering topics. This includes trying to find out news about more traditional ETL tools like Informatica, SAP BODS, and Talend.”