Data Engineer
Well-trained data engineers are crucial for effective data governance and readiness. Learn more about the skills and training required to excel in this exciting role.
Role profile
What does a data engineer do?
Data Engineers focus on building and maintaining data pipelines, mastering tools like SQL, Python, Spark, and ETL processes.
They ensure seamless data flow and accessibility for decision-making. They build and maintain data pipelines, integrate diverse data sources, and create robust ETL processes to prepare clean, reliable datasets.
Data Engineers design scalable systems, optimize performance, and support analytics, enabling teams like Data Scientists and BI Analysts to focus on insights. Their work ensures data is available, accurate, and secure, driving efficiency, innovation, and strategic growth.
Why do businesses need data engineers?
Well-trained and up-to-date data engineers are crucial for effective data governance and readiness. They ensure data is accurate, secure, and compliant with regulations, forming a strong foundation for downstream processes like analytics and AI. By implementing robust pipelines, managing metadata, and automating workflows, they enhance data quality and accessibility. Their expertise in modern tools and practices enables organizations to adapt to evolving technologies, reduce risks, and maximize the value of their data assets, driving better decision-making and innovation.
What are the key skills required to be a data engineer?
- This role typically requires strong proficiency in SQL and Python for building and optimizing data pipelines and managing complex datasets.
- Data Engineers must have experience with big data tools (e.g., Spark, Hadoop) and data workflow orchestration (e.g., Apache Airflow).
- Familiarity with cloud platforms like AWS, Azure, or GCP is highly valued, along with experience in designing scalable ETL processes and maintaining data lakes or warehouses.
What is the difference between a data engineer and data architect?
The role of a data architect is similar to that of a data engineer.
Data Architects work at more of a strategic level, designing data models, structures, and system architecture. They define data governance, scalability, and integration plans. Architects require broader knowledge of systems, business needs, and emerging technologies, while data engineers dive deep into implementation and optimization.
How does QA support data engineer training?
QA offer a broad catalog of training for data engineers, with industry-leading certifications and apprenticeship programs, all delivered by data experts with real-world experience.
Our online learning platform provides access to a wealth of course, exam and hands-on labs which support data engineers in learning new skills and organizations in building their data engineering capabilities.
Our course catalog covers a range of relevant topics for data engineers, including training in programming languages and cloud platforms, such as Databricks, AWS, GCP, Azure.
What might a data engineer also be known as?
A data engineer might also be known as a:
- AI engineer
- Machine learning engineer
- Data architect
- Big data engineer
Data engineer insights
How to become a data engineer
Explore how to become a data engineer with our range of apprenticeships, instructor-led courses and online training.
Learn data engineering skills online
Gain access to unlimited tech training, including data engineering courses and hands-on labs with a subscription to our online learning platform.
Data engineering courses
Learn how to securely engineer the way data is collected, formed and stored, so that you can quickly and reliable analyze and share data, with courses delivered by our experts.
Data engineer apprenticeships
Our Level 5 Data Engineer apprenticeship program is designed to provide learners with a strong foundation for the development of advanced technical competencies.
Top data engineering courses
Fundamentals of Data Engineering
This one-day course shows the history, skills required, theory and technologies behind the Data Engineering role.
Data Engineering with Databricks
This course provides an introduction to data engineering with Databricks, covering key tools and frameworks such as Delta Lake, Databricks Workflows, Delta Live Tables, and Unity Catalog.
Data Engineering on Google Cloud
This four-day instructor-led class provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform.
Preparing for the Professional Data Engineer Examination
This full-day instructor-led course helps prospective candidates structure their preparation for the Professional Data Engineer exam.
Hear from our data expert
"As an aspiring data engineer, you’re building the backbone of how organizations use data. While mastering engineering technologies like data pipelines, ETL processes, and cloud platforms is essential, don’t stop there. Understanding downstream tasks like analytics, machine learning, and reporting gives you a broader perspective of how your work impacts the bigger picture. When you know both the "how" and the "why," you don’t just move data—you shape insights, decisions, and innovations. So, dive deep into your craft but stay curious about the bigger ecosystem. That balance will make you truly exceptional."
Learning Consultant - Data
Databricks training for data intelligence
Maximize your data and AI potential with Databricks. Empower teams to unlock the power of data, drive innovation, and accelerate business growth.
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