Data engineers do the essential “Big Data” groundwork that provides data architects and data scientists with what they need to do their jobs. As well as developing and maintaining the databases and processing systems, they sort the relevant data from the irrelevant.
Data Engineer Job Description Template
It’s an exciting time to be a builder. Constant advances in technology are creating an exciting new world for those who understand the value of data. The role of a data engineer is a supporting one, but it is also an extremely vital one.
As a data engineer, you’ll be handling the design and construction of scalable management systems, ensure that all data systems meet company requirements, and also research new uses for data acquisition. You should also know the ins and outs of the industry such as data mining practices, algorithms, and how data can be used.
In order to be stand out as a candidate, you should express humility and patience. Data engineering is about building the underlying infrastructure, and so being able to pass the limelight to someone else is imperative. We want to see candidates with mechanical tendencies and a desire to know how things work and to improve them. Furthermore, being able to listen to your colleagues is essential.
Data Engineer Responsibilities
- Design, construct, install, test and maintain data management systems.
- Build high-performance algorithms, predictive models, and prototypes.
- Ensure that all systems meet the business/company requirements as well as industry practices.
- Integrate up-and-coming data management and software engineering technologies into existing data structures.
- Develop set processes for data mining, data modeling, and data production.
- Create custom software components and analytics applications.
- Research new uses for existing data.
- Employ an array of technological languages and tools to connect systems together.
- Collaborate with members of your team (eg, data architects, the IT team, data scientists) on the project’s goals.
- Install/update disaster recovery procedures.
- Recommend different ways to constantly improve data reliability and quality.
Data Engineer Requirements
- Bachelor’s degree in computer science, software/computer engineering, applied mathematics, or physics statistics.
- Experience in a related field with real-world skills and testimonials from former employees.
- Possible work experience and proof of technical expertise.
- You may also consider a Master’s degree in computer engineering or science in order to fine-tune your skills while on the job. (Although a Master’s isn’t required, it is always appreciated).
- Intellectual curiosity to find new and unusual ways of how to solve data management issues.
- Ability to approach data organization challenges while keeping an eye on what’s important.
Data Engineer FAQ
What is included in the daily work of a data engineer?
A day on the job in data engineering consists of handling data within the organization, data transformation, and maintaining source systems. Data query might also crop up quite a bit,
Which technical languages should I learn to increase my chances of getting a job as a data engineer?
You should be well-versed in statistics, R and SAS languages machine learning techniques, mathematics, and SQL databases. Python is also the most widely-used programming language across the board when it comes to data engineering. Furthermore, a problem-solving, analytical knowledge of databases will also be a great asset.
What problems might data engineers run into?
Data engineering is probably the most research-extensive role in the organization, and so engineers come across a lot of problems. Some of these problems include the consideration of processors and RAM sizes, whether or not cloud storage will scale and knowing how long it will take to make it possible. Data engineering is part trial and error, and it is your job to diagnose and fix any failures that might occur.