DataOps Engineer Course

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. 🚀

The role of a Data Ops Engineer is versatile and requires a wide range of skills:

🔹 Data pipeline monitoring & automation – Ensuring that data processes run smoothly, efficiently, and at scale.
🔹 Data quality & performance optimization – Implementing monitoring solutions for data validation, error detection, and performance enhancement.
🔹 Collaboration with data teams – Working closely with Data Engineers, DevOps specialists, and Business Analysts to ensure stable and optimized data workflows.
🔹 Database & cloud integration – Managing cloud and on-premise data infrastructures with a focus on automation and scalability.

Depending on the company size and structure, the tasks of a Data Ops Engineer can vary – from Infrastructure-as-Code (IaC) and data orchestration to optimizing DevOps processes for data workflows.

Engineers focus on making data processes and infrastructures efficient and reliable:

✅ Data monitoring – How can data pipelines be continuously analysed and optimized?
✅ Automation – Which tools and scripts help minimize repetitive processes?
✅ Error handling & scaling – How can it be ensured that pipelines are stable, fault-tolerant, and future-proof?
✅ Security & compliance – How can data protection policies and security standards be met?

📌 Want to learn more about the role of a Data Ops Engineer? Click here! 🚀

🚀 Developed by experts: Created by DevOps and Cloud specialists in collaboration with leading companies – no external providers or pre-made content.

📚 Curriculum:

– Linux & Automation (Bash, Kubernetes, Jenkins)
– Monitoring & Observability (Prometheus, Grafana, Datadog)
– Cloud & Infrastructure as Code (AWS EC2, Lambda, CodePipeline)

⏳ 200 hours of training:

– Bootcamp format: 35 hours per week
– Part-time format: 10 hours per week

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:

– Communicating information.
– Presenting and popularizing your work.
– Valuing data through visualizations (especially by creating dashboards).
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.

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:

– Oral presentations of projects, which allow you to develop effective communication and presentation skills.
– Masterclasses focused on project management and interpreting results, to improve your ability to communicate complex technical insights and collaborate across teams.
These elements ensure that you not only gain technical expertise but also excel in managing and presenting your work in real-world environments.

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”.

Once you have registered on the website, a member of our team 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.
Prior to entering the course, you will have to take a technical placement test. This test covers basic data analysis and statistics.
Then, a member of our admissions team will contact you to communicate the results and discuss your motivations and the relevance of your project. Up to this point, there is no commitment with DataScientest, and you can decide at any time not to proceed.
The registration phase only begins once the project has been confirmed. From that moment on, our teams will organize your Data Ops Engineer bootcamp or continuous training and provide you with information on all its practical aspects.
Access time : Until the day before the start date, subject to availability.

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.

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!

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. 🚀

To find all the financing possibilities, nothing could be simpler: we have created a page dedicated to the subject ! 

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.