If you do a quick search on the most attractive job role in the post-pandemic scenario, Data Engineer would unanimously emerge as the winner. Data Engineering is a very promising field that also offers a rewarding career. With leaders like Google, Twitter and Tesla among many others producing massive amounts of data, one can only imagine the huge volume of big data being made available on a daily basis. With the help of Big Data Technologies, data engineers ensure that the huge amount of data that is being processed at a fast speed is transformed and transferred to the destination where it will be efficiently and securely stored and used, as needed.
If you look at the statistics, the number of interviews for jobs in the field of data engineering has shot up by 40% between 2020 and now. Moreover, there has been an enormous growth in funding in the field of data engineering, along with an increase in companies that offer internships in data engineering. Want more reasons to excel in this promising field? Read on to find out the skills you would be requiring to become a Data Engineer.
Role of a Data Engineer
The field of Data Engineering is an expansive field that covers a variety of job roles wherein Data Engineers act as facilitators for pure and clean data from various sources that can be utilized at companies to make informed decisions. Data engineers are accountable for capturing data and presenting the information in a way that is simple to understand and evaluate.
Though this sounds like a relatively easy task, the role of a Data Engineer usually involves building, testing and maintaining high-quality data in order to meet the goals of an organization. Experienced data engineers gain several transferable knowledge, including the architecture of systems, programming and interface, as well as the configuration of sensors. Their work routines shift frequently and include creating data pipelines, using predictive models, cleaning data and more.
The typical tasks of a Data Engineer include the following:
Data exploration and analysis
Data extraction from a vast collection of unfiltered data
Cleaning and evaluation of data sets
Writing and preparing ETL logic
Managing data pipelines that distribute across several servers
Mining and query data
Stitching data together
Creating data stores
Optimizing the delivery of data
Normalization of data and modeling
Redesigning the data infrastructure for the possibility of scaling
Making use of the framework to provide data
Aiding the data scientist in the process of optimizing products
Key Skills Required
Wondering what kind of skills companies look for in data engineers applying for an entry-level position? Well, you need to learn the fundamentals. Interviews at the junior or intern level won't need you to know more than the three sections listed below:
Python
SQL
Data modeling and development of ETL
You should also be able to upskill and develop your capabilities in the below-mentioned sections:
Programming language - Python, SQL, Java, etc.
Databases SQL and NoSQL built on
ETL/ELT Technologies Apache Airflow, Hadoop
Cloud computing and Infrastructure
Streaming - Apache Beam
Data Engineer Jobs
Becoming a Successful Data Engineer
Earn a bachelor's degree from the field of your choice
The majority of data engineers have an undergraduate degree in mathematics, science or other related fields to establish solid foundations. By studying the art of software engineering, you'll be able to comprehend the basics of programming and become capable of obtaining work at an entry level. It is possible to take on tasks to gain practical experience and build an impressive portfolio for future work.
Master relevant skills
Develop your knowledge of programming fundamentals as well as databases and big data abilities. Start by learning SQL fundamentals as it is necessary to use SQL to search data. Additionally, you should learn to create models of data, employ databases, build data pipelines and perform data mining. You also need to learn how to process large amounts of data streams. Also, you can study different tools such as Kafka and Hadoop to manage workflows in the Big Data ecosystem.
Gain additional certifications
You'll require additional professional certifications in order to further your career in the field of data engineering. You could choose to pursue an advanced master's degree that includes the field of data engineering as a specialization or certificates that provide specific technical expertise such as automation or scripting Java, Kafka and Tableau distributed systems.
Learn the key technologies
The two key technologies you need to focus on are Python and Scala. For successful software development, you may need to improve your skills in these languages as well as gain practical experience. There are many online courses that provide the certifications required for programming languages. Being able to demonstrate expertise in programming languages like Java, C++, Python and Scala are sought-after by employers.
Master cloud computing
It is vital to know how to operate seamlessly using cloud computing in current times. It is possible to learn various kinds of services provided by cloud platforms such as cloud storage cluster management and data processing management computation among many others.
Grow professionally
The most effective way to grow professionally is to keep up with the most recent trends and developments related to data science. Keep an eye out for the latest software launches as well as new data engineering tools. Work diligently and create a portfolio that will show your technical abilities in order to get the desired position within a well-known company.
Data is everywhere and the role of an engineer in data is vital to make the most of the power of data within any company. The main advantage of this profession is its high pay with the median salary ranging between $65,000 and $135,000. If you enjoy tidying up raw data as well as being a data wrangler who prefers working in a peaceful environment, then the field of data engineering is the right job for you.
If you need personalized guidance in your quest to choose data science as your career path, HiCounselor can help you get started on the right track.
HiCounselor has forged technical advances to transform the hiring landscape for job seekers and recruiters alike. Our career accelerator program provides job seekers with coaching and mentorship from industry leaders employed at FAANG companies while recruiters ally with HiCounselor to empower their hiring strategy and hone in on the best candidates. Learn more about HiCounselor here and reach out to us on LinkedIn, Facebook and YouTube.
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