The demand for Data Engineering jobs is on the rise and the positions are filling as expected. Hence there is a high demand and good pay for the job. If you’re looking to know what skills are required for data engineer then you’re on the right page.
Many people pursue a data science career without understanding the role of a Data Engineer. Data Engineer is a combination that lies between data science and software engineering. However, the data engineer is crucial and relies majorly working on programming languages.
In this article, we will cover everything there is to be known before enrolling in the Data Engineering course of pursuing a career in it. Below are the major things that we will cover:
- Job Description of Data Engineer
- Difference between Data Engineer and Data Scientist
- Skills required to become a Data Engineer
- Best certification course to learn Data Engineering
Job Description of Data Engineer
Data Engineer is a highly technical position that requires essential technical skills such as programming languages, mathematics, and knowledge of computer science. Their major role is to manage and organize the data without impacting the daily business operations.
While the data engineer’s roles and responsibilities may vary among the different organizations, there are few that remain common. Some of the common responsibilities across all the organizations are listed below:
- One should design and develop the data architectures that are suitable for business operations
- Test and maintain different types of architectures
- Extract date from one source and load to a different source with no errors
- They should be able to develop data set processes and efficient in data acquisition
- Implementing, verifying, and designing software systems
- Use programming languages on a daily basis
- Work on multiple languages to write scripts
- Find new ways to use the existing data and learn new ways to extract data
- Improve the data efficiency, data quality, and reliability
- Able to address business issues by using large data sets
- Prepare data for prescriptive and predictive modeling
- Find ways to automate the tasks by using existing data
These are some of the common roles and responsibilities of a data engineer however it is not limited to the above.
The difference of Data Engineer and Data Scientist
Before you choose your profession to become a data engineer, it is essential to understand the difference between Data Engineer and Data Scientist.
The goal of a data engineer is to develop and maintain different types of data architectures such as databases. This is because data engineer usually deals with the raw data which includes human errors. Such type of data is unformatted and non-validated. The job of a data engineer is also exciting and challenging every day.
The main focus of the Data Scientists is that they have to clean and organize the data before analysis and perform prediction. Once the data passes the initial round of cleaning and manipulation it will then be provided to the data scientist. Finally, they will process this data before it is imported into machine learning algorithms. The job of the Data Scientists is exciting and spontaneous every day. If this role excites you then you can check out the best courses to learn Data Science.
What Skills are Required for Data Engineer?
To become a Data Engineer, one needs to learn several technologies and we’ve listed all the technical skillset here.
1. Programming Languages to Learn for Data Engineer
It is crucial and essential to learn programming languages to become a data engineer and one should learn this first before working on any of the data engineering tools. If you are already aware of programming language then we suggest you brush up on the syntax to be aware of the foundations of the programming languages.
You will be to focus on one of these two programming languages Python and Scala. However, we highly recommend that you start with Python because it is the simple and easiest programming language to learn. If you learn Python it would come in very handy in learning both data science and machine learning.
If you are aware of other programming languages such as C++, Ruby, or JAVA then it’s an added advantage on your resume.
Here’s a list of best programming languages to learn for Data Engineer.
2. Learn Everything about Database
Every data engineer should know a way around working with every kind of data and this requires working on various tools. This is the most basic requirement of every data engineer as this involves collecting, store, and run a query from the database.
SQL is the simplest and easiest technical skill set to learn and you can finish learning in about 1-2 weeks completely. SQL is used to build and manage relational database systems.
Learning to manipulate database management systems (DBMS) is a must-learn for every young data engineer enthusiast. This can be achieved by taking the top course on SQL/MYSQL. We’ve listed the best SQL courses to learn online and you may find this very useful.
3. Data warehouse architecture
Every company out there needs to work on data warehousing and ETL job activities and this filled by a data engineer. Data warehouses are used to store huge volumes of data for query and analysis using the tools such as Microsoft Azure, Amazon Redshift, Google BigQuery, and more.
Since there is a high demand for cloud technologies many entry-level positions of data engineer also expect you to be familiar with AWS cloud services or Microsoft Azure or Google Cloud Platform.
Along with the above skills, ETL also comes in handy. ETL refers to extracting data from a source, convert it to the required format for analysis, and load it into the data warehouse. Working on ETL tools will give you more exposure and experience on the skillset.
4. Apache Hadoop and Apache Spark
One is also expected to have a strong background in Apache Hadoop and Apache Spark. Hadoop is the most essential skill a data engineer has, Apache Hadoop software library is a framework that allows for distributed processing of large data sets. Since Hadoop is designed to scale up from a single machine to many machines, it is best used for the distributed processing of huge data sets.
Apache Hadoop frameworks support programming languages like Python, Java, R, and Scala. Hence it is one of the most powerful tools in Big Data.
Apache Spark is a data processing engine that is used to perform the same functions as Hadoop, and it supports stream processing. This can be achieved in Hadoop as well but uses batch processing. Hence, one needs to know both these technical skills and must have work on Hbase, Mapreduce, or Hive.
5. Foundations of Machine Learning
You are also expected to know the foundations of machine learning and its algorithms. Python is the programming language this is highly preferred in data science and machine learning. Machine Learning helps ever data scientists to make a prediction based on both the historical and current data.
However, as a data engineer, you don’t need to learn everything about machine learning but a foundation is necessary as it enables them to understand the need of data scientists. This also helps to create accurate data pipelines.
6. Data Structures and Algorithms
The Data Structures and Algorithms also play a vital role for every data engineer. The basic knowledge of algorithms will help data engineers to understand the big picture of the organization’s end goal. With this, a data engineer can focus on the best data filtering and data optimization techniques.
The key here is to understand the importance of data structure and algorithms.
How to Become a Certified Data Engineer?
The good thing about pursuing a data engineer certificate course is that it’s a new field and there are no formal required educational backgrounds. However, it will help you if you have a degree in mathematics, statistics, computer science but not necessary. Anyone can pursue to become a data engineer.
The best way to learn data engineering is to take an online data engineer certificate course. This helps the recruiter to that you’ve got the necessary skills to fulfill the job’s requirement.
Below is the best certification course to learn data engineering from scratch:
Become a Data Engineer by Udacity
Data Engineering with Google Cloud – Coursera
Data Science and Engineering with Spark – edX
Data Engineering, Big Data, and Machine Learning on GCP Specialization – Coursera
In case if you’re wondering how long does it take to become a data engineer, it entirely depends on how soon you pick the course and stick to the course material and its curriculum. It is always recommended that you study for at least 1-2 hours per day.
Salary of a Data Engineer
The Data Engineer profession offers the highest average salary of around $110,000 to $155,000 depending on the experience, skills, and location where you live. As you gain more and more experience in the field you will move to a senior position where your salary will range from $152,000 to $194,000 per year.
Summary: How to be a Data Engineer?
The only way to become a data engineer is to learn the technical skillset mentioned in this post and take the recommended course. We always recommend the best learning resources to help students like you achieve their personal career goals.
The path to becoming Data Engineer may look hard and tough but it is well worth it and finally pays off when you become one. We hope that we answer your question on what skills are required for data engineering.
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