What is a Data Engineer
A Data Engineer is one of the most sought-after IT roles. Responsible for Python, Spark, Airflow. Demand grows year after year.
Required skills
- Python
- Spark
- Airflow
- dbt
- Snowflake
- Kafka
- SQL
EITT training path guides you step by step.
Career progression
- Foundations (0-6 mo) — basics: Python, Spark
- Junior (6-18 mo) — first projects
- Mid (2-3 yr) — independence
- Senior (4+ yr) — architecture, leadership
Salary
Data Engineer rates in Poland 2026:
$4,500-9,000/mo
Frequently Asked Questions
What is the difference between a data engineer and a data analyst?
A data engineer builds and maintains the infrastructure that makes data analysis possible, including pipelines, data warehouses, and ETL processes. A data analyst uses that infrastructure to query data and generate insights. Data engineering is more focused on software engineering and architecture, while analysis is more focused on statistics and business interpretation.
Which cloud platform should I learn first for data engineering?
AWS is the most widely adopted cloud platform with the largest market share, making it a safe first choice. However, Azure is dominant in enterprise environments, especially in Europe. Learn one platform deeply and understand the core concepts, as they transfer well across providers. Most employers value cloud-agnostic thinking.
Do I need a computer science degree to become a data engineer?
A degree is helpful but not required. What matters most is strong proficiency in Python, SQL, and distributed systems concepts. Many successful data engineers are self-taught or come from bootcamp backgrounds. Building a portfolio with real ETL pipeline projects and earning certifications like AWS Data Engineer Associate can compensate for a lack of formal education.
How important is Apache Spark for a data engineer in 2026?
Spark remains one of the most important tools in the data engineering ecosystem for processing large-scale datasets. While newer tools like dbt and Snowflake handle many use cases, Spark is essential for big data workloads and real-time processing. Most senior data engineering roles expect Spark proficiency.
Training investment pays back in 3-6 months.
Start with EITT
EITT offers a complete Data Engineer training path — from basics to senior level. 500+ experts, 2,500+ trainings, 4.8/5 rating.