🚀 Think you’ve got what it takes for a career in Data? Find out in just one minute!
Get a recognized certification, benefit from individual support until employment, and secure a flexible, in-demand job as a Data Ops Engineer.
During your Data Ops Engineer training, you will complete a 120-hour project.
The goal: Apply your knowledge in a real project of your choice and gain valuable practical experience for your portfolio. 🚀
Combining flexible learning on a platform and Masterclasses led by a Data Scientist, this mix has attracted more than 6000 alumni, and gives our training courses a completion rate of +98%!
Our teaching method is based on learning by doing:
A Data Ops Engineer ensures the smooth operation and automation of data pipelines. They monitor and optimize data workflows, ensure data quality, and use monitoring and orchestration tools to enable a reliable and scalable data infrastructure for business intelligence and analytics.
Monitor data pipelines and ensure they run smoothly and reliably.
Automate data processing tasks to ensure efficiency and scalability.
Optimize workflows, performance, and security of DataOps platforms.
Integrate data sources and ensure seamless collaboration between development and operations.
A user-friendly, comprehensive interface for a tailor-made learning experience. An enhanced platform and premium coaching.
If you live in France, you can benefit from several financing options:
Don’t hesitate to make an appointment with one of our advisors to find the funding that best suits you!
If you are living in Germany you have multiple ways to finance your training courses depending on your professional situation.
Employees:
Your company may also be able to benefit from the Qualifizierungschancengesetz and get funding from the state.
Unemployed, job seekers, self-employed or students:
Get more information about the process and the next steps by downloading our Bildungsgutschein guide.
The DataScientest team will help you find the best funding for your personal circumstances.
Different types of financing can be applied depending on your current situation:
For further information, please check this page and book an appointment with our team.
Jobs in the field of Data Engineering are constantly evolving. That’s why it’s important to clearly define each role in order to understand the current needs of businesses and tailor the training to the job market.
One of these in-demand roles is the Data Ops Engineer. Check out the full job description and learn more about the required skills, tools & technologies, career prospects, and salary expectations. 🚀
New technologies generate massive amounts of data every day. One of the biggest challenges for companies is to efficiently manage, monitor, and deliver this data to ensure a reliable data infrastructure for strategic decision-making. This is where the Data Ops Engineer comes in – a key role in Data Engineering that ensures the smooth operation and automation of data processes.
To identify the key skills for a Data Ops Engineer in 2024, we surveyed 25 Data Managers from leading companies. The most frequently requested skills are:
✅ Data integration and workflow automation
✅ SQL, NoSQL, and database management
✅ DevOps and DataOps tools (Kubernetes, Terraform, Airflow, dbt)
✅ Cloud platforms and big data technologies
✅ Soft skills: problem-solving, communication, and systems thinking
The goal of a Data Ops Engineer is to ensure a powerful, scalable, and stable data infrastructure. The best way to achieve this? Practical training that equips you with the most in-demand skills and tools.
🔍 Explore the role of a Data Ops Engineer in detail: tasks, core competencies, career prospects, and salary expectations. Or read our blog article by clicking here. 🚀
Once registered on the site, a member of our teams will contact you to discuss your background and your professional project. This is to ensure that the training you want to follow is consistent with your expectations.
Before starting training, you will have to pass a technical positioning test. It covers mathematical notions of probability/statistics and basic algebra (level L1/L2 mathematics).
Then, a member of our admissions team contacts you to communicate the results and discuss your motivations and the relevance of your project. So far, there is no commitment with DataScientest and you can therefore decide at any time not to continue your steps.
The registration phase only begins once the project has been confirmed. From that moment, our teams take care of starting your Data Ops Engineer bootcamp or your continuous education and organizing it with you in all its practical aspects, whether it is continuing professional training or in bootcamp format.
To combine flexibility and motivation, DataScientest’s pedagogy is based on hybrid professional training. This makes it possible to combine flexibility and rigor without compromising on one or the other. A 100% distance training combining synchronous (masterclass) and asynchronous times (courses and exercises on the ready-to-code platform) so that motivation is always there. This translates into 85% learning on the coached platform and 15% masterclass session by videoconference.
The courses are given by videoconference but the follow-up remains the same with teachers available and attentive to your progress throughout your training.
By the end of our Data Ops Engineer training, you will be able to:
✅ Configure and manage virtual environments with Vagrant and Linux
✅ Master Linux administration and Bash scripting
✅ Set up and optimize web servers like NGINX efficiently
✅ Use Kubernetes and DevOps tools for Continuous Integration & Deployment (CI/CD)
✅ Manage automated deployment processes with GitLab and Jenkins
✅ Apply monitoring and logging tools like Prometheus, Grafana, and Datadog
✅ Understand cloud technologies and manage AWS services like EC2, EBS, Auto Scaling, and ELB
✅ Use AWS Lambda, CodePipeline, and API Gateway for cloud-native DevOps processes
✅ Automate infrastructure with AWS CloudFormation
🚀 Start your journey as a Data Ops Engineer today!
To enroll in the Data Ops Engineer training, you should meet the following requirements:
✅ English skills at a B1 level
✅ Passing the corresponding eligibility test
✅ Completed Bachelor’s degree in Computer Science (Business or Applied Computer Science), Mathematics, or Natural Sciences, or at least 2 years of professional experience in data processing/data analysis
✅ A computer with internet access and a webcam
These requirements ensure that you fully understand the concepts of the Data Ops training and are optimally prepared for the course. 🚀 Start your journey today!
🚀 Developed by experts: Created by DevOps and Cloud specialists in collaboration with leading companies – no external providers or pre-made content.
📚 Curriculum:
⏳ 200 hours of training:
The assessment of the results is done through the implementation of an evaluation procedure, allowing to determine if the learner has acquired the necessary skills for the role of Data Ops Engineer.
There are two aspects evaluated by the educational team:
Professional role-playing incorporating the development of a project with an estimated duration of 120 hours.
Online practical cases to regularly evaluate your skills.
By the end of our Data Ops Engineer training, you will be able to:
✅ Configure and manage virtual environments with Vagrant and Linux
✅ Master Linux administration and Bash scripting
✅ Efficiently set up and optimize web servers like NGINX
✅ Use Kubernetes and DevOps tools for Continuous Integration & Deployment (CI/CD)
✅ Manage automated deployment processes with GitLab and Jenkins
✅ Apply monitoring and logging tools like Prometheus, Grafana, and Datadog
✅ Understand cloud technologies and manage AWS services such as EC2, EBS, Auto Scaling, and ELB
✅ Use AWS Lambda, CodePipeline, and API Gateway for cloud-native DevOps processes
✅ Automate infrastructure with AWS CloudFormation
🚀 Start your journey as a Data Ops Engineer today!
Throughout your training, and as your skills develop, you will conduct a Data Ops Engineer project.
You will carry out a project in a group with other members of your class. Our topics are updated monthly and are inspired by the work we do in companies. You can also propose a personal project, as long as the data is accessible, and our teaching team validates it.
Obviously this adds difficulty and also realism to make you fully operational: uncleaned data, untrained models, but our teachers are there to help you at each step of this project.
It is an extremely effective way to move from theory to practice and to ensure that you apply the topics discussed in class.
It is also a project that is highly appreciated by companies because it ensures the quality of the training and the knowledge acquired at the end of the Data Ops Engineer training. Skills that are not only technical, since soft-skills are also highlighted:
In short, this is a project that will require a real investment: one third of your time spent on the training will be spent on the project.
Each major step highlights a new aspect covered in the course. The project is supervised by a project mentor to guide and coach you.
Our certification is issued by The Sorbonne University in Paris. By completing our Data Ops Engineer training, you will receive an official certificate of the French university, Paris-Sorbonne. This will greatly enhance your resume for future job applications.
To find all the financing possibilities, nothing could be simpler: we have created a page dedicated to the subject !
If you want to know how to make architectural decisions in accordance with AWS, this is the certification for you! Earn the status of “AWS Certified Solutions Architect Associate”.
Mastering DataOps is a crucial skill across many industries. As businesses increasingly rely on efficient data management, automation, and optimization of data pipelines, the expertise gained in this training opens doors to new opportunities, enhances problem-solving abilities, and boosts career growth—whether you’re in IT, finance, marketing, operations, or analytics. This training equips you with the essential skills to automate data processes, ensure reliability, and drive innovation across sectors, making you a key player in transforming business data operations.
A Junior Data Ops Engineer earns between €40,000 and €50,000 per year, depending on the industry and company.
With 3+ years of experience, salaries rise to €55,000–€65,000, and senior Data Ops Engineers with advanced skills can earn €70,000–€80,000+ annually.
Sources: GermanTechJobs.de, SalaryExpert.com. 🚀
For Data Managers in large companies, it’s often more important for a Data Ops Engineer to have strong communication skills—both written and oral—than to master the company’s specific data infrastructure. That’s why we’ve incorporated modules into our curriculum that help you enhance these soft skills through:
These elements ensure that you not only gain technical expertise but also excel in managing and presenting your work in real-world environments.
Newsletters developed by our data scientists are sent regularly and are a reliable source of specialized data science information.
At the same time, the DataScientest community continues to grow, and with it all of its alumni.
To keep in touch and allow former students to communicate with each other, DataScientest has set up a group of alumni on LinkedIn who share and discuss various themes around Data Science.
Questions, tips, and technology news are shared on this page for the benefit of all. You will be invited to join it at the beginning of your training. Also on the agenda: are business opportunities, networking, and events (trade shows, Data Challenges…).
This has made it possible to create strong links with the major groups, which have ensured the growth of our structure.
Initially, DataScientest supported the data transition of companies. This has made it possible to create strong links with the major groups which have ensured the growth of our structure.
Thanks to our experience with large companies, we regularly organize recruitment fairs for all our students and alumni with our partner companies.
New technologies generate massive amounts of data every day. One of the biggest challenges for companies is to efficiently manage, monitor, and deliver this data to ensure a reliable data infrastructure for strategic decision-making. This is where the Data Ops Engineer comes in – a key role in Data Engineering that ensures the smooth operation and automation of data processes.
To identify the key skills for a Data Ops Engineer in 2024, we surveyed 25 Data Managers from leading companies. The most frequently requested skills are:
✅ Data integration and workflow automation
✅ SQL, NoSQL, and database management
✅ DevOps and DataOps tools (Kubernetes, Terraform, Airflow, dbt)
✅ Cloud platforms and big data technologies
✅ Soft skills: problem-solving, communication, and systems thinking
The goal of a Data Ops Engineer is to ensure a powerful, scalable, and stable data infrastructure. The best way to achieve this? Practical training that equips you with the most in-demand skills and tools.
🔍 Explore the role of a Data Ops Engineer in detail: tasks, core competencies, career prospects, and salary expectations. Or read our blog article by clicking here. 🚀
Once registered on the site, a member of our teams will contact you to discuss your background and your professional project. This is to ensure that the training you want to follow is consistent with your expectations.
Before starting training, you will have to pass a technical positioning test. It covers mathematical notions of probability/statistics and basic algebra (level L1/L2 mathematics).
Then, a member of our admissions team contacts you to communicate the results and discuss your motivations and the relevance of your project. So far, there is no commitment with DataScientest and you can therefore decide at any time not to continue your steps.
The registration phase only begins once the project has been confirmed. From that moment, our teams take care of starting your Data Ops Engineer bootcamp or your continuous education and organizing it with you in all its practical aspects, whether it is continuing professional training or in bootcamp format.
To combine flexibility and motivation, DataScientest’s pedagogy is based on hybrid professional training. This makes it possible to combine flexibility and rigor without compromising on one or the other. A 100% distance training combining synchronous (masterclass) and asynchronous times (courses and exercises on the ready-to-code platform) so that motivation is always there. This translates into 85% learning on the coached platform and 15% masterclass session by videoconference.
The courses are given by videoconference but the follow-up remains the same with teachers available and attentive to your progress throughout your training.
By the end of our Data Ops Engineer training, you will be able to:
✅ Configure and manage virtual environments with Vagrant and Linux
✅ Master Linux administration and Bash scripting
✅ Set up and optimize web servers like NGINX efficiently
✅ Use Kubernetes and DevOps tools for Continuous Integration & Deployment (CI/CD)
✅ Manage automated deployment processes with GitLab and Jenkins
✅ Apply monitoring and logging tools like Prometheus, Grafana, and Datadog
✅ Understand cloud technologies and manage AWS services like EC2, EBS, Auto Scaling, and ELB
✅ Use AWS Lambda, CodePipeline, and API Gateway for cloud-native DevOps processes
✅ Automate infrastructure with AWS CloudFormation
🚀 Start your journey as a Data Ops Engineer today!
To enroll in the Data Ops Engineer training, you should meet the following requirements:
✅ English skills at a B1 level
✅ Passing the corresponding eligibility test
✅ Completed Bachelor’s degree in Computer Science (Business or Applied Computer Science), Mathematics, or Natural Sciences, or at least 2 years of professional experience in data processing/data analysis
✅ A computer with internet access and a webcam
These requirements ensure that you fully understand the concepts of the Data Ops training and are optimally prepared for the course. 🚀 Start your journey today!
🚀 Developed by experts: Created by DevOps and Cloud specialists in collaboration with leading companies – no external providers or pre-made content.
📚 Curriculum:
⏳ 200 hours of training:
The assessment of the results is done through the implementation of an evaluation procedure, allowing to determine if the learner has acquired the necessary skills for the role of Data Ops Engineer.
There are two aspects evaluated by the educational team:
Professional role-playing incorporating the development of a project with an estimated duration of 120 hours.
Online practical cases to regularly evaluate your skills.
By the end of our Data Ops Engineer training, you will be able to:
✅ Configure and manage virtual environments with Vagrant and Linux
✅ Master Linux administration and Bash scripting
✅ Efficiently set up and optimize web servers like NGINX
✅ Use Kubernetes and DevOps tools for Continuous Integration & Deployment (CI/CD)
✅ Manage automated deployment processes with GitLab and Jenkins
✅ Apply monitoring and logging tools like Prometheus, Grafana, and Datadog
✅ Understand cloud technologies and manage AWS services such as EC2, EBS, Auto Scaling, and ELB
✅ Use AWS Lambda, CodePipeline, and API Gateway for cloud-native DevOps processes
✅ Automate infrastructure with AWS CloudFormation
🚀 Start your journey as a Data Ops Engineer today!
Throughout your training, and as your skills develop, you will conduct a Data Ops Engineer project.
You will carry out a project in a group with other members of your class. Our topics are updated monthly and are inspired by the work we do in companies. You can also propose a personal project, as long as the data is accessible, and our teaching team validates it.
Obviously this adds difficulty and also realism to make you fully operational: uncleaned data, untrained models, but our teachers are there to help you at each step of this project.
It is an extremely effective way to move from theory to practice and to ensure that you apply the topics discussed in class.
It is also a project that is highly appreciated by companies because it ensures the quality of the training and the knowledge acquired at the end of the Data Ops Engineer training. Skills that are not only technical, since soft-skills are also highlighted:
In short, this is a project that will require a real investment: one third of your time spent on the training will be spent on the project.
Each major step highlights a new aspect covered in the course. The project is supervised by a project mentor to guide and coach you.
Our certification is issued by The Sorbonne University in Paris. By completing our Data Ops Engineer training, you will receive an official certificate of the French university, Paris-Sorbonne. This will greatly enhance your resume for future job applications.
To find all the financing possibilities, nothing could be simpler: we have created a page dedicated to the subject !
If you want to know how to make architectural decisions in accordance with AWS, this is the certification for you! Earn the status of “AWS Certified Solutions Architect Associate”.
Mastering DataOps is a crucial skill across many industries. As businesses increasingly rely on efficient data management, automation, and optimization of data pipelines, the expertise gained in this training opens doors to new opportunities, enhances problem-solving abilities, and boosts career growth—whether you’re in IT, finance, marketing, operations, or analytics. This training equips you with the essential skills to automate data processes, ensure reliability, and drive innovation across sectors, making you a key player in transforming business data operations.
A Junior Data Ops Engineer earns between €40,000 and €50,000 per year, depending on the industry and company.
With 3+ years of experience, salaries rise to €55,000–€65,000, and senior Data Ops Engineers with advanced skills can earn €70,000–€80,000+ annually.
Sources: GermanTechJobs.de, SalaryExpert.com. 🚀
For Data Managers in large companies, it’s often more important for a Data Ops Engineer to have strong communication skills—both written and oral—than to master the company’s specific data infrastructure. That’s why we’ve incorporated modules into our curriculum that help you enhance these soft skills through:
These elements ensure that you not only gain technical expertise but also excel in managing and presenting your work in real-world environments.
Newsletters developed by our data scientists are sent regularly and are a reliable source of specialized data science information.
At the same time, the DataScientest community continues to grow, and with it all of its alumni.
To keep in touch and allow former students to communicate with each other, DataScientest has set up a group of alumni on LinkedIn who share and discuss various themes around Data Science.
Questions, tips, and technology news are shared on this page for the benefit of all. You will be invited to join it at the beginning of your training. Also on the agenda: are business opportunities, networking, and events (trade shows, Data Challenges…).
This has made it possible to create strong links with the major groups, which have ensured the growth of our structure.
Initially, DataScientest supported the data transition of companies. This has made it possible to create strong links with the major groups which have ensured the growth of our structure.
Thanks to our experience with large companies, we regularly organize recruitment fairs for all our students and alumni with our partner companies.
Want to learn more about our training ?
