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Are you looking for a structured and battle-tested approach for learning data engineering?

Would you like to have a seasoned expert guide you through the course and answer all your questions?

Do you want to grow your skills together with a small cohort, and have AMAs with world-class guest speakers every week?

The course covers the most relevant and essential data and software engineering topics that enable you to start your journey as a professional data engineer or analytics engineer. The curriculum and its delivery are defined by our core values: sustainability, transparency, pragmatism and collaboration.

You bring curiosity, motivation, some experience with Python and SQL, and willingness to get your hands dirty. We bring the rest.

Course formats and Structure

You can choose from two course formats: the full-time course and the part-time course, the latter is mainly catering for participation from the Americas (7-11am EST) or from the Asia-Pacific region (8-12pm CST). Click here for upcoming course dates.

Time commitment
Tuition fee


12 weeks live online

40 hours/week

Mon-Fri, 9am-5pm CET

Access to all data engineering course materials and assignments
Prepwork, career coaching and placement support, communications training, expert guest speakers, capstone project



9 weeks live online

20 hours/week

Mon-Fri, 1-5pm CET /
7-11am EST/ 8-12pm CST

Access to all data engineering course materials and assignments
Prepwork (to be completed before the course launch), expert guest speakers, capstone project (optional)


The part-time program is basically a compressed version of the full-time one. The main difference between the experiences is the amount of time that you allocate to your assignments and learning, but every participant has access to the same course materials. We recommend the full-time course for anyone who’s schedule allows participating in it, however we understand that full-time employees can’t dedicate more than four hours on a daily basis. Full-time and part-time participants learn together in the same cohort.