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CAREER PATH · 6 courses

Data Engineer

Move into data engineering: model data properly, build pipelines that run without you, work in the cloud, and process data at scale, up to the data behind AI.

About 6 months, up to two courses at a time. 6 courses, 36 live one-on-one sessions, 54 hours with your trainers.

The job

A data engineer makes sure the right data reaches the right people and systems, on time and in a state they can trust. They design the tables and models, build and schedule the pipelines that extract, load and transform data, run them in the cloud, test the data before anyone uses it, and keep the whole thing reliable and affordable as volumes grow. More and more, they also prepare the documents and data that AI systems answer from.

Why now

Data engineering is still growing in France while the executive job market as a whole is shrinking. Employers look for people who can do more than query data: they want pipelines that run, in the cloud, at scale. This path is built for analysts and developers moving into that role.

The journey

  1. STAGE 1 · FOUNDATIONS

    • Advanced SQL & Data Modelling

    • Python for Data Pipelines

    Both courses run at the same time.

  2. STAGE 2 · CLOUD

    • Cloud Fundamentals: Azure or AWS, and Sovereign Cloud

  3. STAGE 3 · ORCHESTRATION AND TRANSFORMATION

    • Orchestration & Transformation: Airflow, dbt & Data Quality

  4. STAGE 4 · SCALE AND DATA FOR AI

    • Lakehouse & Spark: Databricks, Snowflake & Fabric

    • RAG & Context Engineering

    Both courses run at the same time.

Who it's for

  • Data and business analysts who write SQL and want to build the pipelines behind their reports
  • Developers who move data between files, APIs and databases and want to do it properly
  • Analytics engineers and BI developers who want the full data engineering toolkit
  • Junior data engineers who learned on the job and want a complete, modern method

Before you start

Comfortable with basic SQL (SELECT, GROUP BY, simple joins) and basic programming, ideally in Python (variables, functions, loops, lists and dictionaries). No cloud or big data experience is needed. Data from your own work, or a public dataset close to it, to use during the courses is strongly recommended.

What you'll be able to do

  • Write advanced SQL you can trust and speed up, and design normalised and star schemas
  • Build Python pipelines that extract, load and check data reliably, tested and containerised
  • Deploy and run a secure, cost-controlled workload on Azure or AWS
  • Orchestrate pipelines with Airflow and transform and test data with dbt
  • Build a lakehouse and process data at scale with Spark and streaming, and build RAG systems that answer from your own documents

Certificates

A certificate of completion for each course, and a path certificate, “Data Engineer”, once all six courses are done.

Questions

How long does the path take?

About 6 months, taking up to two courses at a time. You can also go one course at a time, which takes longer.

How much SQL and programming do I need?

The basics: simple queries with joins and grouping, and simple Python scripts. The path takes you from there.

Azure or AWS?

You choose at the start of the cloud course. The concepts are taught once, with the names on both sides.

Can I take a break?

Yes, between two courses. Inside a course, the usual session rules apply.

In which language?

English or French, chosen at the start for the whole path: sessions, documents and certificates.

Will this get me a job?

Nobody can honestly promise that. The path builds the skills employers ask for today, and leaves you with a portfolio you can show.