Price per person
-- (excluding VAT)
Duration of this course
4 days
Course dates
21 - 19 may 2026
15 - 19 june 2026
Data Engineer
In this training, you will develop reliable data pipelines using Python and SQL, integrate various data sources, and automate data processes. You will build scalable data architectures with a focus on performance and data quality. Data engineering forms the technical backbone of modern data-driven solutions.
Throughout the course, you will work hands-on with designing and maintaining databases, performing ETL processes (Extract, Transform, Load), and manipulating and transforming data. Pipeline optimization is also covered. Theory is combined with practical assignments, enabling you to apply best practices directly and avoid common pitfalls.
You will learn
- How to design and manage relational databases using SQL
- How to clean and manipulate data using Python
- How to build and automate ETL processes
- How to set up and maintain scalable data architectures
- How to ensure data quality in data-driven environments
Topics
- Introduction to relational databases and SQL
- Overview of database types
- Various RDBMS systems and SQL dialects
- Data types and keys
- Introduction to SQL
- Retrieving, sorting, and filtering data
- Writing advanced SQL queries for data engineers
- Grouping and aggregating data
- Subqueries
- Joins
- Inserting, updating, and deleting data
- Creating, altering, and dropping tables
- Python fundamentals
- Introduction to Python for data engineering
- Variables, data types, lists, and dictionaries
- Logic, functions, and methods
- Python packages for data engineers
- Using package NumPy for efficient data structures
- Using package Pandas for cleaning, manipulating, and automating data
Visualizing data with Matplotlib
Who should attend?
This course is intended for (beginning) data engineers, data analysts, BI specialists, and other professionals looking to broaden or deepen their knowledge of data engineering.
Prior knowledge
No specific prior knowledge is required. However, some experience working with data is helpful.
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