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 organisations to adapt to evolving technologies, reduce risks, and maximise 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.
Data architect insights
How to become a data engineer
Data engineer training
Explore how to become a data engineer with our range of apprenticeships, instructor-led courses and online training.
If you're a business looking to upskill your team, or hire a data apprentice, get in touch with our team to discuss your requirements.
Build your data engineering skillset
Upskill with instructor-led training
Explore data engineering apprenticeships
Earn a data certification
Insights from the experts
"As an aspiring data engineer, you’re building the backbone of how organisations 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
Useful reads on data
Let's talk
Start your digital transformation journey today
Contact us today via the form or give us a call