Working in the realm of big data is an outstanding career option. The job openings for data engineers have increased by 30 % over the last five years, much more than the average rise witnessed throughout the country. According to Glassdoor, data engineers make more than $110,000 annually. Before entering a field, it is good to understand what to anticipate, even though employment growth and income are both enticing. Here’s everything you need to know about the data engineer job to start your career.
As highly compensated information technology specialists, data engineers must know several applications and procedures. Therefore, acquiring and refining these skills may make you a competent data engineer and a more desirable applicant.
Coding is a highly regarded ability that is required for the vast majority of data engineering jobs. Numerous organisations want employees with at least a fundamental grasp of programming languages such as:
- Python
- Golang
- Ruby
- Perl
- Scala
- Java
- SAS
- R
- MatLab
- C and C++
Data warehouses and ETL enable businesses to use extensive data in a meaningful way. Data that originates from a variety of sources are standardised via this process. The process is known as ETL, which stands for “Extract, Transform, and Load,” collects data from various sources, transforms it so it can be analysed, and then feeds that data into the warehouse. Several prominent ETL tools include Talend, Informatica PowerCenter and AWS Glue.
Data engineers should have a comprehensive grasp of database administration. Since Structured Query Language (SQL) is the most popular option, obtaining a thorough understanding is tremendously beneficial in this profession. SQL is a database programming language that retrieves and maintains table-based data. You should also get familiar with alternative database technologies, such as Bigtable or Cassandra, particularly if you want to engage in freelance data engineering work.
Even though machine learning is generally the domain of data scientists, it might be advantageous for data engineers to have at least a fundamental grasp of its use. Building your expertise in data modelling and statistical analysis will enable you to develop solutions that can be used by peers and make you an invaluable addition to any firm.
As a data engineer, you are required to be able to communicate with coworkers who may or may not have technical competence. Because of this need, having excellent communication skills is quite crucial. Although you often collaborate with other data specialists, such as data scientists and architects, you are generally required to discuss your results and recommendations with non-technical colleague
Many ambitious data engineers choose to disregard it, thus depriving themselves of greater employment chances. The significant advantages of writing for data engineers are as follows:
- Enhance your knowledge. According to Ian Goodfellow, a data engineer at Apple, writing blogs helps to consolidate and deepen the comprehension of complicated professional topics.
- Clarify complicated facts for others. You may be responsible for reporting data and outcomes to supervisors, team members, and other parties, which demands clear and succinct writing.
