It’s 2020, the right time to upgrade your big data career!
Have you ever wondered how you end up in the jobs you end up in? Why you had missed on those opportunities you once set your hearts on? Perhaps, if you look back and do a reality check, it will likely be something that has been neglected.
Our lives are built upon fictional constructs, the ones who’re lucky become the winner or you can say they are occasionally the perfect fit for the job.
As the big data industry gets bigger, job skills in big data and data analytics will grow at an accelerating rate.
When this kind of randomness takes place – our skills, talents, quirks, experiences, and traits become the topmost priority for employers looking to hire individuals to fill the skill gaps. But what happens if you do not have the right set of skills?
Nearly 40 zettabytes of data will be stored by the end of the year, as predicted by Researchgate. You definitely need the right set of skills to analyze such a huge volume of data. The reason why a big data career will be proven beneficial.
One of the greatest challenges recruiters face is the number of job applications they receive. Despite receiving several portfolios and resumes’, the right set of talent is difficult to seek.
Data is valuable for every organization. Since 2015, the rate at which jobs in the big data industry is seen to have an annual growth of around 34%.
Looking at the increasing demand for big data engineers, organizations are now focusing on individuals with the latest big data skills.
Here’s a glance at the topmost important big data skills: –
- Python and SQL
Both Python and SQL were found to appear at over two-thirds of every job listing. Consider yourself lucky if your fluency in these programming languages is superb.
Python is a common and popular language amongst recent developers and engineers today. It is widely used in the field of big data and data analytics. Most preferred programming languages by AI professionals as well.
While SQL (Structure Query Language) is functional for removing data out of relational databases. SQL is an old skill that has found its relevance in the tech market.
- AWS (Amazon Web Services)
AWS has been seen in around 45% of the job listings. Being a cloud computing platform, it already made its presence known in the job market.
Spark has been seen in almost half of the job listings out there. It is said to be a unified analytics engine that initiates big data processing, graph processing, machine learning, SQL, and built-in modules for streaming.
- Hadoop and Java
Hadoop and Java are seen to be at over 40% of the job listings out there.
Based on Stack Overflow’s 2019 Developer survey, Java was found to be the commonly used and the 10th most dreaded. And Python was found to be the second most loved programming language.
- Apache Hive, a data warehouse that helps is managing, reading, and writing large datasets
- Apache Hadoopmakesuse of the MapReduce programming model to sever large volumes of big data
- Apache Kafka is a popular streaming platform that helps in ingesting streaming data
They are non-relational, horizontally scalable, and unstructured databases that help in retrieving or storing data.
One of the most popular programming languages in the field of big data analytics.
Based on several kinds of research made AWS was found to have the largest number of job listings and have appeared in more than 25% of the job listings for big data engineers as compared to data scientists.
This skill also appeared in near about 45% of the job listings that were made for professionals in big data industry and around 20% listings for data scientists.
Some of the less common skills for data engineers: –
Though these skills are not quite important, it is still mandatory for big data engineers to acquire.
SAS though less amongst the data engineers has a difference of near about 14% job listings. It is mainly used for statistics and data.
R programming showed the largest drop in the skillset of a data scientist to a data engineer. It had a drop rate of nearly 17% instead of 56%. R is used for statistical analysis and is popular among academicians and statisticians.
Based on a study by IDC (Worldwide Big Data and Business Analytics Market), the analytics field itself is poised to grow to USD 203 billion by the end of 2020.
Growing businesses and enterprises will need more experts who are data-savvy. As the world undergoes data explosion and proliferation of digital devices, there will be an increasing need for big data engineers in the foreseeable future.