One of the key members of a data science team is a data engineer. A Data Engineer is a person, fully equipped with knowledge of hardware, databases, data processing at scale and computer engineering and who can build data infrastructure, manage data storage and use and Implement production tools.
What does a data engineer do?
Data engineers might do things like build infrastructure. So, they would build out your databases and the hardware for that. Data engineers also work with big data. They are basically responsible for developing, constructing, testing and maintaining databases and large-scale data processing systems. Often times, Data engineers may work very closely with data architects who determine what data management systems are appropriate They also work together data scientists who determine which data are needed for analysis. They might also run ETL (Extract, Transform and Load) on top of big datasets and create big data warehouses that can be used for reporting or analysis by data scientists. As Data Engineers focus more on the design and architecture, they are typically not expected to know any machine learning or analytics.
What skills do they need?
They might need knowledge of right hardware to be looking for in terms of storage and as well as in terms of computing. They do need to have knowledge about database software also. They should to be able to interact with the data scientists in your organization. Data Engineer will inform the hardware choices that they’re going to make to solve your problem. They must understand data processing at scale because almost always now organizations are collecting a massive amount of data.
Qualifications & Skills
The background for data engineers is often computer science and computer engineering, but they could also come
from other places. They might come from a different background with some computer science experience that they completed maybe in online courses or in courses in person. Or maybe they come from information technology
where they’ve actually been involved in infrastructure building and so forth.
A data engineer can be from any background like:
- Computer Science and Engineering
- Information Technology,
- Computer Science
He should be having very strong knowledge in database technology and data warehousing.
There are a few key things that they need to know. They might need to know about how to build and manage some databases,things like SQL, things like MongoDB. They might also need to know how to do things like implement or run things like Hadoop, which is a parallel processing infrastructure. Now it’s not necessarily true that they need to know any one of these buzzwords or another. But it is true that they need to have the combination of skills that allows them to build out a data infrastructure that’s supportive and that can be maintained.
Hadoop, MapReduce, Hive, Pig, Data streaming, NoSQL, SQL, programming.
DashDB, MySQL, MongoDB, Cassandra
If you are the person having these skills then easily you can get into Analytics field with a Data Engineer designation.
Also Read Who is a Data Scientist?