We are living in a world, rather, a tech world where data is considered as gold today. Data has really become precious as every smallest decision is made on the basis of what data reveals.
There is no doubt that data science roles, specifically data engineers(or Big Data Engineers), are in demand across every industry. Data Engineers are crucial to the Big Data revolution and are tasked with building, testing, and maintaining data architecture.
It is expected that we will produce 463 exabytes of data each day by 2025. Isn’t that enormous?
As long as there is data to be processed, the demand for data engineers will continue to grow. In fact, LinkedIn considers the role of Data Engineer as one of the jobs that will be on the rise in 2021.
To bring out the difference in the world of big data and make the life of Data Scientists easier, you can choose to make your career as a Big Data Engineer. Data Engineering is all about collecting, storing, analyzing, and interpreting data at scale. Organizations today are capable of collecting huge amounts of data but they require the right candidates and the technology to make sure that the data is readable and usable when it reaches data analysts and data engineers.
Let us discuss those 5 things that you should know to make a career as a Big Data Engineer.
What is a Data Engineer?
Typically, data engineers develop systems that are capable of collecting, managing, and transforming raw data into a user-readable format for business analysts and data scientists to interpret. The ultimate goal of a data engineer is to make data accessible such that senior data workers can utilize it to evaluate and optimize their performance.
Some common tasks that a Data Engineer is responsible for are:
- Create data sets that align with the requirements of business
- Build algorithms so as to transform data into an actionable and usable format
- Develop, test, and support architectures of database pipelines
- Collaborate with management teams to understand the main objectives of the company
- Develop new methods for data validation as well as data analysis tools
- Ensure data compliance with security policies and data governance
5 Things to Know for Making a Career in Data Engineering
1. You have to be a Strong Developer.
Everything is code today: pipelines as code, infrastructure as code, etc. So, you need to develop coding skills. You may be required to develop systems that are complex and difficult.
Common programming languages that you need to master are NoSQL, SQL, Java, Python, R, and Scala.
2. Acquire the data engineering skills
Apart from acquiring coding skills, other skills that you need to develop are:
- ETL systems: ETL or Extract, Transform, and Load is the process that allows you to move data from databases and other locations to a single repository or data warehouse. Xplenty, Alooma, Stitch, and Talend are some of the most popular ETL tools.
- Relational and Non-relational databases: These are the most common solutions meant for data storage.
- Automation and Scripting: being a data engineer, you have to master the concepts of automation and scripting to work with data for organizations.
- Big Data Tools: working with Big Data requires you to master Big Data tools; the most popular ones include MongoDB, Hadoop, and Kafka.
- Machine Learning: to understand the requirements of data scientists in your team, you should know at least the basic concepts of Machine Learning techniques.
- Data Security: Though data security teams may be there in an organization, you might still be required to maintain data security to protect it from theft or loss.
3. Go Hands-on
It is always good to go hands-on to learn any technology. Education is always good, but experience can make you perfect.
4. Social and Communication Skills are crucial.
Some of the soft skills you need to acquire are:
- Attention to detail: when building pipelines, it is important to keep data quality in consideration. So you have to take care of every detail to maintain the quality and integrity of data.
- Appreciation for good design: to become a good data engineer, you should appreciate the simplicity and elegance of the design and are not over-architected.
- Excellent communication skills (both verbal and written): the most important task of a data engineer is to cleanse and interpret data in a format that is readily usable. For this, you need to acquire excellent communication skills in both verbal and written aspects.
- The eagerness of working with the server-side systems: you are not really required to work on the design or front-end of an application as a data engineer. So, you have to stay eager or excited about working with back-end systems.
- Love for learning: An Engineer has to keep on learning always. Data Engineer is no different. You have to stay updated with new libraries, tools, and frameworks in the market. Also, the world of Big Data is ever-evolving, so it can be beneficial for you if you have a love for learning.
5. Get Certified
Certification serves as a testimonial that validates your knowledge and skills to potential employers and the excellent way to pass the certification exam is by taking up an online training course.
When you go through preparation for a certification exam, you generally go hands-on with real-life projects and validate your skills to your recruiters. Some of the certifications you can opt for are:
- Associate Big Data Engineer
- IBM Certified Big Data Engineer
- Cloudera Certified Professional Big Data Engineer
- Google Cloud Certified Professional Data Engineer
Today Big Data is changing the way people do business, thereby creating a demand for data engineers who can gather and manage huge quantities of data.
If you are willing to pivot to a new career, start acquiring skills that are job-ready for the role of a Data Engineer.
This can be done by taking up an online training course, where you get options to choose from different learning modes, self-paced learning, learner’s assistance, exposure to real-life projects, doubt-sessions, and career guidance.