The data engineer is increasingly becoming the much wanted allrounder in the Big Data field. Whether it is building pipelines, or checking out platform issues, the data engineer should be able to fix it. On the other side there is no official schooling to become a data engineer. Experience outweighs education and there is definitely more than one learning path to become a data engineer. How do you know if you have found the real expert? Well, maybe by using this checklist.
1. A data engineer must convert raw data into usable data for your Data Scientist
No data scientist can turn company’s data into insights without great data engineering behind the scenes. The Data Engineer needs to be able to understand what kind of data the Data Science team needs and be able to prepare and deliver it.
2. The Data Engineer should be able to develop your Data Platform
The core job of a data engineer is the creation of data pipelines that reliably and efficiently serves up relevant data for analysis. Ingesting all that data and turning it into something usable is a major challenge.
To be able to do this first and foremost the data engineer needs to be an excellent developer. How else is he or she going to be of use? Python, Java and Scala are currently the most used languages. The engineer should be completely comfortable with relational and non-relational databases, cloud infrastructure and distributed systems. In addition, they need to master Big Data tools like Hadoop, Spark, and Airflow to make the process of extraction, transfer, and loading (ETL) of data easy and automated.
3. Social and communication skills are important
A data engineer is almost always part of a team. So hiring someone who is brilliant in technical skills, but is impossible to team up with, is not going to work. The time of the nerd technician is over, social skills are probably as important nowadays as the technical skills (though this may differ per company). Being able to present plans and ideas to various business units and executive leaders is always important.
4. A data engineer is open to new challenges and is willing to constantly learn and improve
Finally, no day is the same for a data engineer. He/she needs to be able to understand a lot of things. Quite often he or she will face unknown challenges which means he/she must be able to learn quickly and adapt this new knowledge into a fitting solution for the problem. More in general technologies to optimize the use of data are still in rapid development. To remain relevant, a data engineer must keep up with the newest technologies and improvements in his field. Coping with stress and having an open mind are clear requirements for the job.
Are you looking for a junior data engineer with the right technical knowledge and experience? Every year, we identify a select group of promising developers whom we train to become junior engineers. They start with an intensive seven-week bootcamp and then embark on a year-long traineeship with one of our clients. The traineeship is customized to meet the technologies used by the client, and throughout the traineeship, our trainees are guided by a mentor from LINKIT. Download the one-pager for more information about the bootcamp, the skills that data engineers possess, and what they can bring to your company.
