Despite the hit triggered by COVID-19 pandemic, hiring professionals with top tech skills are still on the rise.
Though these are uncertain times, employers thrive to hire technologists with updated tech skills. Technology is ever-increasing, from big data to data science and the Internet of Things to artificial intelligence and machine learning, the future world needs every skilled individual who can lay hands on these new technologies.
The need for data science and big data analytics is increasing, but people who can technically understand business risk are the ones needed. With data generated daily, the data available for companies to analyze is abundant. For companies to make use of data, they need big data engineers. Individuals from these fields must demonstrate skills and knowledge the industries are currently looking to hire for.
Amid the COVID-19 crisis, let us look at the most trending skills big data engineers must learn by the end of 2020.
Below are the top technologies from the big data engineer job listing in January 2020.
- Python: the most widely used programing language while working with a lot of data and scripting. Also, an ideal tool for all data science professionals.
- SQL: Structured Query Language (SQL) is widely used to remove data out of a relational database. SQL has been around for quite some time now and has indeed shown its resilience over the years. SQL and Python have been seen listed at almost two-third of the job listings found on the internet.
- AWS: Amazon Web Services (AWS) is seen in at least 43 percent of the job listings for big data engineers. It is one of the largest market share found on a cloud platform.
- Hadoop: This constitutes 40 percent of the job listings. An open-source software framework that allows us to store data and run applications on a large amount of commodity hardware.
- Apache Hadoop: with the help of the MapReduce programming model helps server data for big clusters. Besides this follows Scala, Apache Hive, NoSQL, and Kafka. Each of these skills was found in the data engineer listings.
- Scala: Scala that was built along with Spark has been a popular programming language among big data enthusiasts for quite some time now. According to Stack Overflow 2019 Developer Survey report proclaims Scala to be the 11th dreaded language.
- Apache Hive: it is a data warehouse that initiates reading, writing, and managing large datasets from the distributed storage.
- NoSQL: these are non-relational, unstable, and unstructured databases that facilitate big data storage and access needs.
- Kafka: Kafka being a distributed streaming platform is widely popular for ingesting live stream data.
The most common keywords found in a big data engineer job listings
AWS had the largest used keyword (25 percent) that appeared in the job listings for data engineers more than data science professionals. This keyword showed up to nearly 45 percent of the data engineer job listings.
Terms that are crucial for both data science and big data analytics
In addition to the list mentioned above, below are the most common data engineer terms you will come across while seeking for jobs in the big data realm.
Thankfully, there are multiple big data engineer certification programs found available online for breaking into a career in big data. You can have a rough look at the most priority technologies you can learn as a beginner. If you end up getting into any one of the programs, make sure you learn the below order of big data skills.
If you’re learning SQL, it is recommended for you to learn PostgreSQL because it is popular, growing, and above all it is open-source.
Once you’ve gained knowledge in Python, the next step is to learn Pandas, a Python library that helps in cleaning and manipulating data. If you’re looking to become a big data engineer, it is recommended that you learn Python libraries such as Pandas.
Acquiring in-depth knowledge in AWS is an added advantage as the demand for data engineers skilled in cloud computing skills outstrips the supply.
A word of advice
Even if the economy slows down, there hasn’t been much change in the technology field. According to experts, job roles such as big data engineers, data scientists, AI engineers, and machine learning engineers will remain reliable and in-demand.
According to the U.S. Bureau of Labor Statistics, data-related careers will increase by 12 percent by 2028. This sums up to having 546,200 newer big data jobs within the same timeframe. As experienced, big data has transformed businesses and has helped the economy grow. Thus, people with the required skillsets in big data will remain in demand.