“In God we trust, all others bring data.” — W. Edwards Deming
Who exactly is Data Engineer?
Systems for large-scale data gathering, storage, access, and analytics are designed, built, and optimized by data engineers. They provide data pipelines that data scientists, apps that focus on data, and other data consumers use.
Do you have any doubts about taking a course to become one?
Some of you may believe that learning the fundamentals can be done for free online through YouTube or other resources, which is partially accurate. Even without a formal education, many engineers excel. But if you want to hone your abilities, broaden your knowledge, or begin working as a data engineer, you might also want to think about getting a master’s degree in computer engineering or computer science.
To your relief, though, not every position calls for a master’s degree in data engineering. Some businesses will accept relevant work history and documentation of technical proficiency in place of a higher degree.
Responsibility:
The creation of high-performance algorithms, predictive models, and proofs-of-concept, as well as the development of data set processes required for data modeling and mining, are all aspects of the highly strategic work of data engineering.
Here is a list of the duties of a data engineer:
a. Ensuring that data storage and gathering systems adhere to approved industry standards and business requirements.
b. Incorporating new data management software into an organization’s current systems or investigating fresh data collecting options. This can entail assisting a business in devising a fresh approach to effectively gather information from a brand-new consumer.
c. Combining several systems using unique software components made with a variety of tools and languages, such as scripting languages, or building a solid analytics infrastructure to assess the data kept by a company.
d. Preserving data security while processing and storing it. Data engineers continue to be the first line of defence for a company’s cyber defences, putting in place and maintaining disaster recovery procedures as well as suggesting strategies to increase data reliability and quality.
Taking on the role of a data engineer might present an opportunity to work directly with data architects, modelers, and IT specialists to accomplish various project objectives.
Degrees and Concentration
What you know will matter a lot more than your degree, or even whether you earn one at all, if you want to join the ranks of data engineers. If you have the funds and credentials required to study in Europe, you’ll discover more data engineering degrees there than there are at the undergraduate or graduate levels in the US. Instead of seeking for degrees in data engineering, search for degrees in computer science, information systems, data science, big data, and analytics that allow students to concentrate in data engineering.
Your degree’s name won’t be as important as the program’s substance. Look for programs that provide electives or core courses that are concentrated on:
- Relational and non-relational database theory and practice
- Data modeling techniques
- Programming
- ETL design
- Database clustering techniques
- Architectural projections
Further accreditation or education for a data engineer
The key to being a successful data engineer is having the necessary technical abilities. Learning to use any high-tech tools and programming languages that weren’t included in a degree programme is a common component of continuing education for data engineers. Employers of data engineers frequently want prior experience with:
- Hadoop/Hive
- Java/Scala
- Spark
- Kafka
- SQL and NoSQL
- Python
- Cloud platforms like AWS
- Algorithms and data structures
- Distributed systems
- Tableau
- ElasticSearch
- Data warehousing and ETL tools
- Machine learning
- UNIX, Linux, and Solaris
You probably won’t find a bachelor’s degree programme or even a master’s degree programme that will teach you everything you need to know to become a data engineer unless you want to pursue a degree in data engineering. The good news is that you may take online courses at websites like Udemy to get the knowledge and abilities you’ll need. You will be guided by these courses as you pick up relevant programming languages and get practical expertise with the most popular data engineering tools.
Data engineers can also earn certifications, however there aren’t many of them. Typically, they are tool-specific, like:
- Google’s Cloud Data Engineer Certification
- Cloudera’s Certified Professional Data Engineer credential
- Microsoft’s Certified Solutions Associate in Data Engineering with Azure credential
- Microsoft’s MCSE: Data Management and Analytics credential
- IBM’s Certified Data Engineer credential
Typical advancement path for a data engineer
The position of data engineer is not often entry-level. The majority of hiring managers favour applicants with extensive coding and data-related experience.
Think again if you believe that being an analyst is the best route to this position. Few data analysts make the switch to become data scientists, despite the fact that many do so. The majority of data engineers begin their careers as software engineers because this field is all about creating tools, frameworks, and infrastructure from scratch.
You will likely follow this career path for promotion whether you switch to data engineering or start looking for work immediately out of college.:
- Junior data engineer
- Data engineer
- Senior data engineer
- Lead data engineer
- Head of data engineering
- Chief data officer
If you wish to work in data engineering but lack any experience in software engineering or analytics, work on one or more projects that show off your skills.
Job outlook for data engineer
There are several prospects for employment and professional advancement in data engineering, which is a field that is expanding across all industries. A study by IBM indicates that over the next three years, demand for data scientists and engineers would rise by 28%. For people who desire to work in data engineering or science, these are promising chances. The industries of banking, insurance, information technology, and professional services will account for about 59% of the available jobs. The study also discovered that there is a greater need for data engineers than for data scientists. Data engineers create and maintain the infrastructure that ensures data security and efficient data movement, which is the main cause of this. As a result, businesses are seeking experts who can assist them in facilitating the safe and efficient transfer of data across all networks.
An organization’s data systems are designed, developed, and maintained by a data engineer. The work is highly specialised, pays well, and offers lots of opportunity for advancement. A career in data engineering may be the ideal fit for you if you have a strong interest in math, programming, and computers.
Pros and cons of becoming a data engineer
The fact that this work pays well is arguably the biggest pro. While a data engineer’s annual compensation might range from $64,000 to $132,000, the average salary for a data engineer is roughly $91,000.
The fact that data engineers are in high demand is another major benefit. As of this writing, Indeed.com had over 100,000 job vacancies for data engineers (roughly ten times the number of open data scientist jobs).
The fact that being a data engineer isn’t one of the more attractive careers in data science may be its worst drawback. The people who get to deliver data-driven solutions to stakeholders are data scientists and data analysts. As a result, they are the rockstars of the data science field, together with the Big Data analytics specialists. The data engineers, who make it all possible while laboring in the background, rarely receive the same level of credit.
