Data Engineer training – the complete guide: prerequisites, program, opportunities

A Data Engineer training provides access to the highly sought-after job of data engineer. Discover everything you need to know through our complete guide: prerequisites, skills to acquire, salaries and job opportunities, best existing training…

To analyze and take advantage of data, Data Scientists need access to it at all times. It is necessary to set up “reservoirs” of data, a storage and processing architecture, and “pipes” allowing to filter the data at the source. This is the role of the Data Engineer , essential within a Data Science team.

Contents

  • What is a Data Engineer or Data Engineer?
  • Data Engineer skills
  • Salary and training opportunities
  • How to become a Data Engineer?
  • What are the existing trainings?

What is a Data Engineer or Data Engineer?

The Data Engineer develops, builds, tests and maintains databases , collection and processing systems, and “pipelines” continuously delivering data to data scientists and analysts.

This role can vary greatly from one company to another. Generally speaking, the Data Engineer can be seen as the gatekeeper and “facilitator” of data transfers and storage. Its responsibility is to transform the data into a format suitable for analysis .

Among his responsibilities, the Data Engineer must ensure that the data collection and storage systems meet business needs and industry standards. He must integrate the Data Management software into the existing structure of the company or find new ways to acquire the data.

Using a wide variety of programming languages ​​and tools, he creates custom software components to merge different systems or develop an analytical infrastructure. Finally, the data engineer is in charge of storing and processing data securely through cyber defense measures.

Data Engineer skills

A Data Engineer masters the programming languages ​​allowing him to explore data and perform queries within databases. Languages ​​such as Python or R are widely used for statistical analysis or modeling.

It also uses SQL language and engines like Apache Hive, because Big Data data is usually stored on relational databases. Proficiency in tools such as Spark, Hadoop or Kafka is also a valuable asset.

In addition, knowledge of database architectures, Machine Learning, Data Warehousing are very useful. The Data Engineer must also know how to build data pipelines , master Data Mining and use Cloud platforms such as Amazon Web Services.

In general, Data Management technologies are constantly evolving . It is therefore important for the data engineer to constantly monitor developments in the sector and stay up to date.

Salary and training opportunities

The Data Engineer is more and more sought after in all sectors, while Big Data is becoming more and more important. Job openings are plentiful , and will continue to increase over the coming years. According to the Bureau of Labor Statistics, job openings are expected to grow 15% per year through 2029.

Every business, from Silicon Valley giants to small, family-run SMBs now needs a data engineer. This expert is essential to take full advantage of the data available.

As a result, the salaries offered are particularly attractive. According to Glassdoor, a Data Engineer earns an average of $130,000 per year in 2021. In France, the average annual salary is €45,000 .

How to become a Data Engineer?

Typically, Data Engineers have a degree in math, science, computer science, software engineering, or related to the industry in which they work. A Bac+3 level diploma may be enough to access a first job as a data engineer.

In addition, it is absolutely necessary to have concrete experience, such as internships. Those who have chosen to take a course that is not directly related to data engineering must take additional courses. These relate to data structures, algorithms, coding or database management.

Besides, a degree is only the first step to becoming a Data Engineer. It is imperative to have skills in big data, computer engineering and data analysis.

In fact, a first professional experience serves as a springboard, and professional certifications in engineering or Big Data make it possible to complete the baggage. Software companies such as Oracle, Microsoft, IBM and Cloudera offer their certifications. Similarly, the CDMP certification created by the Data Management Association International is widely recognized by employers.

A higher degree in computer engineering, applied mathematics or computer science offers the possibility of reaching a position of responsibility . This is why a large number of Data Engineers choose to continue their studies up to the Master ‘s degree .

What are the existing trainings?

Companies are increasingly seeking Data Engineers. In fact, new formations are emerging. Public universities and private schools now offer data engineering training.

However, it is better to opt for a BootCamp . In fact, this type of training makes it possible to quickly acquire the required skills, and to start working directly.

Those who are already in business and wish to improve their skills or retrain, continuing education is the best option. This approach offers the possibility of learning gradually, while maintaining one’s professional activity or personal projects.

In addition, to complement the knowledge acquired through training, it is possible to gain experience by participating in real-world projects. For example, the Kaggle or GitHub platforms offer collaborative data science projects open to everyone. In addition, many hackathons take place regularly. This is a great way to gain practical experience and enrich your CV or portfolio to convince your future employers!

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