Find

Data Engineers

and Elevate Your Project.

With experts in creating and formatting data sets, your project will be a complete success. Companies rely on the experience of Data Engineers to get important data sorted.

Find

Data Engineers

and Elevate Your Project.

With experts in creating and formatting data sets, your project will be a complete success. Companies rely on the experience of Data Engineers to get important data sorted.

Trusted by Leading Tech Firms

Available Data Engineers

Florian

Data Engineer

Machine Learning

SQL

Power BI

Python

Amelie

Freelance Data Engineer

Tableau

BigQuery

SQL

Python

Benjamin

Data Engineer

C++

Apache

Excel

Power BI

Ina

Freelance Data Engineer

Snowflake

SQL

Redshift

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Hiring

Data Engineers

Made Fast and Simple

1
Free Needs Assessment

In a personal, free needs assessment, we will find a solution to your needs.

2
Receive our Recommendations

We will find a tailor-made match for you that fits your needs.

3
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Time to elevate your product. Meanwhile, ElevateX assists you during the whole project.

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Why ElevateX

Simplicity & Speed

Simplicity & Speed

No fuzz. Simple, fast processes you’ll love.

Tailor-made Matching

Tailor-Made Matching

Work with Data Engineers that exactly match your requirements.
Innovation for the Future Of Work

Innovative & Future-Proof

Be at forefront of the future of work. Tap into the expertise of our IT Professionals to fuel your innovation.

Verified and Checked

Verified & Checked Data Engineers

Less time worrying, more time creating. Work with verified and tested Data Engineers.

Data Engineers Are Highly-Demanded. Future-Proof Your Team.

Frequently Asked Questions

What are

Data Engineers

?

Data Engineers are responsible for ensuring that a company receives all the data and information it needs. These are sorted and put into the desired format. Aspects such as data protection and data security play an important role here.

How do I hire

Data Engineers

?

In a personal meeting we first determine your needs and the skills your perfect Data Engineer should have. In the second step, we find a customized solution. From a pre-selection of experts, you decide on the best candidate. Then you can get started. ElevateX supports you throughout the entire project to guarantee long-term success.

How long does it take to hire

Data Engineers

with ElevateX?

Depending on your technical requirements and availability, you can start working with the Data Engineer as soon as 48 hours.

More About Freelance Data Engineers

What Is the Salary of a Data Engineer?

The average salary for a data engineer is around €60,400 gross per year.  
The range is between a minimum of €50,500 and a maximum of €83,700 gross per year. 

As with other jobs in the IT sector, the salary increases with experience. For example, the salary of a Data Engineer with the title “Head of Data Engineering” can be over €100,000 gross per year.  
A Senior Data Engineer can earn around €77,000, while a Junior Data Engineer earns just over €53,000. 

The average hourly wage for freelance Data Engineers is €117, which corresponds to a daily rate of €936. The high hourly rate is mainly calculated by omitting various payment factors that exist for permanent employees. These include, for example, insurance, vacation days, but also the hardware that is usually provided to permanent employees. 

Other factors that influence the salary are as follows: 

Salary After Graduation 
After completing a bachelor’s degree, the starting salary is €47,500 on average. The starting salary for data engineers with a master’s degree averages €52,780 and for graduates with a doctorate €62,280. 

Salary by Company Size 
The size of the chosen company also plays a decisive role. In a start-up, with fewer financial possibilities, the average salary is around €49,000. In medium-sized companies, it’s €52,250, and in a large company it’s just over €59,000. 

Salary by Industry 
You earn the most as a data engineer in the automotive industry. Here, the starting salary is between around €53,000 and €62,000. The retail sector pays below average with a starting salary of between €44,000 and €51,000. 

Salary by State  
As with most other IT professions, Hesse tops the list with an average salary after entry of between €53,500 and €62,000. The states of Bavaria, Hamburg, and Baden-Württemberg also pay well. 
Rather less is earned in the newer federal states, such as Saxony-Anhalt. 

What Are the Tasks of a Data Engineer?

Data Engineers are responsible for everything that has to do with the creation and maintenance of data. 

Data Engineers provide the data that Data Science experts need for further analysis. Data Engineers receive large and unstructured data sets from various sources. Through pipelines and scripts, Data Engineers get the data into the right format and location. This process is called extract, transform, load (ETL).  

Despite difficult tasks and complex algorithms, data engineers work to keep the code as simple as possible to allow others to easily understand it. 
Data engineers also take care of setting up and monitoring the IT infrastructure.  

Depending on the company, other tasks may also be added, such as purchasing and setting up hardware components with the appropriate software. 

Simply put, data engineers function as the interface between hardware and data processing. This also includes the security and reliability of the entire system. 

Knowledge of data security and data protection is therefore also welcome. 

What Is the Difference Between a Data Engineer and a Data Scientist?

A Data Engineer deals with the preparation of data. They develop, design, test and maintain the complete architecture. A Data Engineer has a strong technical background and has the ability to create and integrate APIs. They have a basic understanding of data pipelines and performance improvements. 

The Data Engineer sorts and structures the unstructured data that the Data Scientist needs for further analysis and interpretation. 

Data Scientists analyze and interpret the complex, digital data that the Data Engineer has previously prepared. For this, they need a deep understanding of statistical data analysis, machine learning, etc…. 
In addition, a Data Scientist also needs extensive industry knowledge in order to put the available data into a meaningful context. In the area of machine learning, the role of the data engineer also does not require such in-depth knowledge as that of the data scientist. 

The tasks and roles of Data Scientists and Data Engineers are quite close to each other. The Data Engineer develops, tests and improves architectures, while the Data Scientist is responsible for creating operational models. Data Scientists are the link between stakeholders and customers. 

In smaller teams, it can also happen that a Data Engineer has to take on several roles, such as Data Analyst. 

Which Skills Does a Data Engineer Need?

Basically, data engineers need knowledge of various programming languages. Probably the most common programming language at this point is Python. In addition, there are tools such as Hadoop, Spark, Hive and Kafka. The query language SQL is also an important skill for the data engineer. 

In addition to skills on various tools and programming languages, a data engineer needs knowledge on various data processes. Knowledge from other or related areas is also important in order to be able to take on further tasks in case of doubt.  

Since data engineers work closely with data scientists and other developer positions, good communication skills and the ability to work in a team are also indispensable. 

What Are the Requirements for a Data Engineer?

As a rule, data engineers can present a university degree. Typical courses of study are the branches of computer science or business informatics.  

However, a university degree is not necessarily a prerequisite.  

You still have the option of making a lateral move through further training or work experience in the field of data engineering.  

However, the chances of a higher starting salary increase with the level of the degree.  

Since the profession is still quite young, there are hardly any opportunities for specialization. However, the role of big data engineer or data architect, for example, is possible. 

The average salary for a data engineer is around €60,400 gross per year.  
The range is between a minimum of €50,500 and a maximum of €83,700 gross per year. 

As with other jobs in the IT sector, the salary increases with experience. For example, the salary of a Data Engineer with the title “Head of Data Engineering” can be over €100,000 gross per year.  
A Senior Data Engineer can earn around €77,000, while a Junior Data Engineer earns just over €53,000. 

The average hourly wage for freelance Data Engineers is €117, which corresponds to a daily rate of €936. The high hourly rate is mainly calculated by omitting various payment factors that exist for permanent employees. These include, for example, insurance, vacation days, but also the hardware that is usually provided to permanent employees. 

Other factors that influence the salary are as follows: 

Salary After Graduation 
After completing a bachelor’s degree, the starting salary is €47,500 on average. The starting salary for data engineers with a master’s degree averages €52,780 and for graduates with a doctorate €62,280. 

Salary by Company Size 
The size of the chosen company also plays a decisive role. In a start-up, with fewer financial possibilities, the average salary is around €49,000. In medium-sized companies, it’s €52,250, and in a large company it’s just over €59,000. 

Salary by Industry 
You earn the most as a data engineer in the automotive industry. Here, the starting salary is between around €53,000 and €62,000. The retail sector pays below average with a starting salary of between €44,000 and €51,000. 

Salary by State  
As with most other IT professions, Hesse tops the list with an average salary after entry of between €53,500 and €62,000. The states of Bavaria, Hamburg, and Baden-Württemberg also pay well. 
Rather less is earned in the newer federal states, such as Saxony-Anhalt. 

Data Engineers are responsible for everything that has to do with the creation and maintenance of data. 

Data Engineers provide the data that Data Science experts need for further analysis. Data Engineers receive large and unstructured data sets from various sources. Through pipelines and scripts, Data Engineers get the data into the right format and location. This process is called extract, transform, load (ETL).  

Despite difficult tasks and complex algorithms, data engineers work to keep the code as simple as possible to allow others to easily understand it. 
Data engineers also take care of setting up and monitoring the IT infrastructure.  

Depending on the company, other tasks may also be added, such as purchasing and setting up hardware components with the appropriate software. 

Simply put, data engineers function as the interface between hardware and data processing. This also includes the security and reliability of the entire system. 

Knowledge of data security and data protection is therefore also welcome. 

A Data Engineer deals with the preparation of data. They develop, design, test and maintain the complete architecture. A Data Engineer has a strong technical background and has the ability to create and integrate APIs. They have a basic understanding of data pipelines and performance improvements. 

The Data Engineer sorts and structures the unstructured data that the Data Scientist needs for further analysis and interpretation. 

Data Scientists analyze and interpret the complex, digital data that the Data Engineer has previously prepared. For this, they need a deep understanding of statistical data analysis, machine learning, etc…. 
In addition, a Data Scientist also needs extensive industry knowledge in order to put the available data into a meaningful context. In the area of machine learning, the role of the data engineer also does not require such in-depth knowledge as that of the data scientist. 

The tasks and roles of Data Scientists and Data Engineers are quite close to each other. The Data Engineer develops, tests and improves architectures, while the Data Scientist is responsible for creating operational models. Data Scientists are the link between stakeholders and customers. 

In smaller teams, it can also happen that a Data Engineer has to take on several roles, such as Data Analyst. 

Basically, data engineers need knowledge of various programming languages. Probably the most common programming language at this point is Python. In addition, there are tools such as Hadoop, Spark, Hive and Kafka. The query language SQL is also an important skill for the data engineer. 

In addition to skills on various tools and programming languages, a data engineer needs knowledge on various data processes. Knowledge from other or related areas is also important in order to be able to take on further tasks in case of doubt.  

Since data engineers work closely with data scientists and other developer positions, good communication skills and the ability to work in a team are also indispensable. 

As a rule, data engineers can present a university degree. Typical courses of study are the branches of computer science or business informatics.  

However, a university degree is not necessarily a prerequisite.  

You still have the option of making a lateral move through further training or work experience in the field of data engineering.  

However, the chances of a higher starting salary increase with the level of the degree.  

Since the profession is still quite young, there are hardly any opportunities for specialization. However, the role of big data engineer or data architect, for example, is possible. 

Data Engineers are responsible for ensuring that a company receives all the data and information it needs. These are sorted and put into the desired format. Aspects such as data protection and data security play an important role here.
In a personal meeting we first determine your needs and the skills your perfect Data Engineer should have. In the second step, we find a customized solution. From a pre-selection of experts, you decide on the best candidate. Then you can get started. ElevateX supports you throughout the entire project to guarantee long-term success.
Depending on your technical requirements and availability, you can start working with the Data Engineer as soon as 48 hours.

Data Engineers Are Highly-Demanded. Future-Proof Your Team.

Future proof your team
Future proof your team