what is a data engineer?
A data engineer is responsible for designing, storing, and maintaining the data within a company. As a data engineer, your job is to gather data, organize it, and make it accessible to employees and consumers. You are also responsible for converting raw data into readable files. Many companies need to make their data accessible for data analytics. It's your job as a data engineer to make the data manageable and readily accessible for management. You may also need to develop data tools for analysis.
Your responsibilities also include building the data library, improving the system so there aren't any crashes, and implementing programs to ensure data privacy. As data builds within a company, you also need to manage the speed and performance of the company's data system. This means constantly cleaning and updating the data system software. As some data systems are online or stored in the cloud, one of your key responsibilities is to prevent hackers from infiltrating the system. Finally, your job is to work with the rest of the management company to determine how your data can improve the company's goals or to solve problems. These responsibilities make your data engineering skills valuable to a company.
Would working as a data engineer suit your interest? Then read on to find out what competencies and qualifications you need to thrive in a data engineer role.
view jobs near youaverage data engineer salary
According to the U.S Bureau of Labor Statistics, data architects have an average salary of $136,540 while Dice Tech Job Report shows data engineers had a 50% year-over-year growth in 2019. The average salary depends on location, your industry, and your experience. Data engineers coming in with experience and more programming skills may command a higher starting salary, and data engineers working in the private sector tend to have higher salaries. Companies in tech typically have a high demand for data engineers, but other industries - such as healthcare and finance - are showing a high need for data engineers as well.
Although an entry-level position often commands lower compensation, there is tremendous growth potential. Data engineers can become senior data engineers or managers, leading teams on data system projects. Data engineers may also become data architects or data scientists, depending on their skills and interests. Or, they may choose to pursue their education further.
Wondering what you can earn as a data engineer? Find out immediately with the Randstad salary checker! You can quickly and easily see what the average salary of a data engineer is.
types of data engineer
There are different types of data engineers, such as big data engineers, cloud data engineers, and data architects. A big data engineer typically focuses on large amounts of data, while cloud data engineers focus on cloud-based platforms. Data architects implement the data system, build stacks, and develop data pipelines. They are also responsible for data diagrams and models. Another type of data engineer is a data integration engineer. Their focus is to integrate data from various sources into one data system. There are specializations, too, such as data security engineers, who specialize in protecting sensitive data.
working as a data engineer
When you work as a data engineer, you're essentially a gatekeeper to the company's data. From creating a data system to ensuring its privacy, your job is to create an effective organization system for the data and to ensure the company's data is safe.
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data engineer job description
What does a data engineer do? A data engineer has to juggle a variety of roles to ensure the company's data system runs efficiently. Although responsibilities will vary based on the company's size and needs, some key responsibilities include:
- data extraction: Extracting data from databases and logs when needed
- data transformation: Cleaning, processing, and transforming raw data into readable formats for employees and consumers
- data integration: Integrating data from a variety of sources into one large data system and ensuring all the data is available in one file
- data storage: Designing and maintaining storage solutions for all the accumulated data, such as NoSQL databases
- data modeling: Creating data models and data analytics for the company to plot progress and implement needed changes
- data pipeline: Managing the data workflow so that the data system runs smoothly and fixing any processing or storage issues
- data security: Developing security measures to keep all the data private
- data monitoring: Monitoring the data frequently and developing safety measures to avoid cyberattacks
- documentation: Keeping detailed documents of all the data in the data system, ensuring there are backups and logs
- data scalability: Finding ways to grow the data system as the accumulated data grows
- troubleshooting: Fixing problems that crop up and immediately finding solutions to crashes or bugs within the system
- updating: Updating all the software frequently to ensure efficiency in the data system
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data engineer work environment
Data engineers usually work in an office. However, as some data is moving to the cloud, there are times when data engineers could work remotely. Data engineers play an important role in both the private and public sectors as data is important in healthcare, the financial industry, education, retail, and more. Companies with large amounts of data frequently have a team of data engineers rather than just one. There are not a lot of travel requirements for data engineers unless the company assigns a project at a different location.
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who are your colleagues?
Data engineers usually collaborate closely with data scientists and data analysts when working on the company's data systems. As a data engineer, you may also get to work with software engineers to update the data system or troubleshoot software issues. The IT department may also collaborate on security issues. The company's management team may want to see data analytics weekly or monthly. Finally, business stakeholders may communicate with you to find out how to implement changes to the company given the current set of data.
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work schedule
Data engineers usually follow a 9-5 work schedule. Remote work is possible, however, especially with a lot of data systems moving to cloud-based technologies. With remote work, you may have more flexibility in terms of when you work. Sometimes, there will be project-based deadlines. This could mean overtime work or work on weekends. If there are troubleshooting issues or the data system crashes, you need to be available immediately to fix any data system problems. There may also be data pipeline failures or security breaches. These kinds of urgent issues can disrupt your regular 9-5 work schedule.
If you are working for a large company and there are several data engineers, there may be different shifts. This could mean working a night shift as opposed to a day shift. If the company has sensitive data, there may be a need to have a data engineer available at all times. In this case, a graveyard shift position may be available.The job outlook for data engineers is promising, and there are quite a few opportunities for growth. For one thing, many companies are transitioning to purely digital. This means all their data is moving to computers and online. This opens up a demand for professionals who can collect, process, and move data from paper to digital storage spaces. With the proliferation of text messages and social media, there is more data that needs processing, organizing, and storing.
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job outlook for data engineer
The job outlook for data engineers is promising, and there are quite a few opportunities for growth. For one thing, many companies are transitioning to purely digital. This means all their data is moving to computers and online. This opens up a demand for professionals who can collect, process, and move data from paper to digital storage spaces. With the proliferation of text messages and social media, there is more data that needs processing, organizing, and storing.
Many companies are also shifting their data into cloud-based storage systems, opening up opportunities for data engineers to learn and adapt to these new systems. There may also be a growing need for data engineers who have cloud technology skills. Big data is another specialization that could be in demand in the future. As large industries, such as the healthcare industry and the financial industry, continue to grow, so will their data. This could create opportunities for big data engineers.
As AI makes its emergence and continues to grow exponentially, so will the need for data engineers well-versed in AI and machine learning. Technology continues to advance, too, and this means new software and new tools continue to emerge. This forces data engineers to adapt, but it also ensures they remain in demand.
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benefits of working for randstad as a data engineer
Working through Randstad offers you a range of benefits:
- being paid weekly
- flexibility
- always a contact person you can fall back on and ask for help from
- many training opportunities
- a range of jobs in your area
Want a permanent contract? But you wonder why it would be interesting for you to work with a staffing company? A temporary job as a data engineer is often a stepping stone to an attractive permanent job. Every year, thousands of people earn a permanent contract with great employers thanks to a temporary job found through Randstad. What's more, many companies recruit their permanent employees through Randstad, too!
data engineer skills and education
Having a well-rounded coding and software education is crucial if you want to be a data engineer. Here are some of the education and programming skills requirements:
- bachelor's degree: A data engineer should have a bachelor's degree in a major such as computer science, math, software engineering, computer engineering, electrical engineering, or a related field. An advanced degree is optional, but you may pursue a master's in fields like data engineering or computer science.
- certifications: The GCP Data Engineer Certification is an important addition to your resume.
programming skills: As a data engineer, you must be fluent in SQL. You should also have an excellent grasp of programming languages. - databases: It's important to gain knowledge of different types of databases. You should also have skills in database design and database management.
- ETL frameworks: ETL (Extract, Transform, Load) frameworks are an important part of data engineering. Knowing frameworks such as Informatica, Apache Spark, and Talend can be helpful.
- big data technologies: Many companies have large data systems, which means big data engineers are in growing demand. Having an in-depth knowledge of data technologies like Apache HBase and Hadoop can be beneficial.
- cloud-based technologies: Many companies are moving their data storage to the cloud. Knowing cloud-based technologies and platforms, such as Azure and Google Cloud, may help you land a job faster.
- data store and warehousing: You should be familiar with platforms like Snowflake, Google BigQuery, and Amazon Redshift.
- version control: It's important to have diverse skills in version control systems. This can be useful for code-based projects.
skills and competencies
In addition to fulfilling the right education requirements, you should have the following skills:
- attention to detail: Data engineering involves a lot of coding and detail-oriented work. It's important to not only build your coding skills but to improve your attention to details.
- problem-solving skills: As a data engineer, you may need to ensure the safety of sensitive data as well as troubleshoot any issues the data systems have. This means you need to resolve issues quickly. You also need to find security patches to prevent hackers from entering the system.
- industry knowledge: If you are a data engineer in a specific industry, it's always beneficial if you learn as much as possible about that industry so that you can tailor your data solutions to the company's specific needs. Healthcare data system needs will differ from an education institution or a bank, for example.
- communication skills: As a data engineer, you work with codes and software. However, it's important to have the skills to effectively communicate any data system issues with management.
- adept at managing projects: Large companies may have a team of data engineers, which could necessitate collaborating on large projects. You may need to be efficient at managing projects from start to finish, ensuring they come in on time and budget.
FAQs about working as a data engineer
Here you will find answers to the most frequently asked questions about data engineers.
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how can I build my data engineering skills?
Some of the key skills you'll need are data management and programming languages. Learn Structured Query Language (SQL) and program languages such as Apache Airflow and Apache Spark. It's also helpful to learn cloud technology and ETL frameworks.
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do I need a data engineer portfolio?
It's a good idea to have a data engineer portfolio that showcases the skills you've gained and the programming languages you're familiar with. If you have developed a data pipeline or you have code-based or content-based projects, you should put together a portfolio that showcases your unique talents.
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what’s the difference between a data scientist and a data engineer?
Data scientists study data to develop algorithms and models while data engineers build data systems that data scientists can use. Although their skills overlap, they play very different roles in a company. Both data scientists and data engineers must be familiar with programming languages, however.
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is a database administrator the same thing as a data engineer?
Although there is some overlap, the two jobs are quite different. A data engineer develops a data system to store the company's data and updates or troubleshoots the system if there are issues. A data administrator, on the other hand, organizes the data and makes the data accessible to clients, customers, and employees.
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what career growth opportunities are available for data engineers?
Data engineers may choose to either specialize or move up into a senior data engineer position. A senior data engineer may take on larger and more complex projects. A data engineer can also become a data engineer manager, which involves overseeing a team of data engineers.
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how do I find a job as a data engineer?
Applying for a data engineer job is easy: create a Randstad profile and search our data engineer jobs for vacancies in your area. Then simply send us your CV. If you do not have a resume, no worries. Just check out our resume builder. This state of the art tool will help you to create your own resume. Need help with your application? Check out all our job-hunting tips!
