The digital age has redefined how businesses operate, and at the heart of this transformation lies data. As organizations grow more data-driven, the role of a data engineer has become critical. The QualCert Level 5 Diploma in Data and AI – Data Engineer offers a comprehensive pathway for professionals aiming to master the design, deployment, and governance of scalable data systems. This internationally aligned qualification bridges advanced data engineering skills with real-world applications in artificial intelligence.
The QualCert Level 5 Diploma is designed for individuals looking to step into or enhance their role as data engineers. This diploma equips learners with in-depth expertise in data architecture, cloud infrastructure, big data technologies, and integrating machine learning models within dynamic data environments. Whether you’re a seasoned IT professional seeking a specialization or a graduate with foundational data knowledge, this diploma will elevate your skillset to meet the industry’s demand for reliable, secure, and efficient data systems.
The demand for skilled data engineers is rapidly increasing. This diploma ensures learners acquire not just theoretical knowledge, but also practical skills they can apply immediately in real-world environments. With a strong focus on cloud technologies, distributed computing, and ethical data practices, learners are prepared to handle modern data engineering challenges with confidence.
Designed with input from industry experts and aligned to international qualification frameworks, the QualCert Level 5 Diploma provides global recognition and career mobility. Learners can expect to gain practical insights through case-based learning, projects, and assessments that reflect real business scenarios.
The QualCert Level 5 Diploma in Data and AI – Data Engineer is more than a qualification—it’s a career accelerator. As industries pivot toward intelligent, automated systems powered by data, the need for professionals who can build, manage, and govern data infrastructure has never been greater.
Course Contents of Level 5 Diploma in Data and AI – Data Engineer
The QualCert Level 5 Diploma in Data and AI – Data Engineer comprises several study units designed to provide learners with a comprehensive understanding. Below is the qualification structure, including the Total Qualification Time (TQT) 600, Guided Learning Hours (GLH) 260, and 75 Credits associated with the program.
| Unit Ref# | Unit Title | Credits | GLH | TQT |
| QC20005- 1 | Data Architecture and Database Design for Scalable Systems | 15 | 60 | 100 |
| QC20005- 2 | Building and Managing Data Pipelines and ETL Processes | 15 | 60 | 100 |
| QC20005- 3 | Cloud Computing and Data Infrastructure Deployment | 15 | 60 | 100 |
| QC20005- 4 | Big Data Technologies and Distributed Computing | 15 | 60 | 100 |
| QC20005- 5 | Integration of AI and Machine Learning Models in Data Pipelines | 15 | 60 | 100 |
| QC20005- 6 | Data Quality, Monitoring, and Governance in Engineering Workflows | 15 | 60 | 100 |
Entry Requirements for the Level 5 Diploma in Data and AI – Data Engineer
To enrol in the QualCert Level 5 Diploma in Data and AI – Data Engineer, learners are expected to meet the following criteria:
Minimum Age
- Learners must be at least 19 years old at the time of enrolment.
Educational Background
- A Level 4 qualification (or equivalent) in a relevant subject such as computer science, data analysis, software engineering, or information technology is recommended.
- Alternatively, a university degree or professional certification in a related technical field may also be considered.
Experience
- Prior professional or project-based experience in working with databases, programming, or data analytics is desirable but not mandatory.
- Candidates with strong practical knowledge of data handling, basic cloud technologies, or software development will benefit most from this course.
Language Proficiency
- Learners must have a good command of English, both written and spoken, to understand technical terminology and participate in assessments.
- For non-native English speakers, a minimum of CEFR Level B2 or IELTS 6.0 (or equivalent) is recommended.
These entry requirements ensure that learners begin the diploma with a solid foundation, enabling them to fully engage with advanced topics in data engineering and artificial intelligence infrastructure.
Learning Outcomes: Level 5 Diploma in Data and AI – Data Engineer
Data Architecture and Database Design for Scalable Systems
- Understand the principles of modern data architecture and database systems
- Design relational and non-relational databases to support scalable applications
- Apply normalization, indexing, and partitioning techniques to optimize performance
- Evaluate architectural models suited for real-time, batch, and hybrid data environments
Building and Managing Data Pipelines and ETL Processes
- Construct end-to-end ETL and ELT pipelines for structured and unstructured data
- Automate data ingestion, transformation, and integration from multiple sources
- Use workflow orchestration tools to manage pipeline execution and dependencies
- Ensure data integrity, consistency, and reliability throughout the pipeline lifecycle
Cloud Computing and Data Infrastructure Deployment
- Deploy scalable data infrastructure using cloud platforms like AWS, Azure, or GCP
- Configure cloud storage, compute, and networking for secure data operations
- Implement Infrastructure as Code (IaC) for automated and repeatable deployments
- Monitor cloud resources to ensure cost-efficiency, availability, and resilience
Big Data Technologies and Distributed Computing
- Apply big data frameworks such as Hadoop, Spark, and Kafka in data workflows
- Design distributed computing strategies for high-volume data processing
- Manage data storage and processing in NoSQL and distributed file systems
- Optimize performance and resource utilization in large-scale data environments
Integration of AI and Machine Learning Models in Data Pipelines
- Embed ML models into production pipelines for real-time or batch predictions
- Use APIs and containerization tools to deploy and scale AI components
- Monitor model performance and retrain workflows for continuous improvement
- Address operational challenges related to model drift, latency, and reproducibility
Data Quality, Monitoring, and Governance in Engineering Workflows
- Implement data validation and profiling techniques to ensure quality standards
- Establish monitoring systems for pipeline health, latency, and data anomalies
- Apply data governance principles to ensure compliance, lineage, and access control
- Develop processes for auditing, logging, and continuous improvement in engineering practices
The QualCert Level 5 Diploma in Data and AI – Data Engineer is tailored for individuals seeking to advance their careers in data engineering, infrastructure design, and AI integration. It is ideal for professionals who want to develop the technical expertise needed to build, manage, and optimize data systems that support modern analytics and intelligent applications.
This course is suitable for:
- Aspiring data engineers who want to gain hands-on experience in data pipelines, big data, and cloud infrastructure
- IT and software professionals looking to transition into data-focused engineering roles
- Database administrators and analysts seeking to expand their capabilities in distributed systems and data architecture
- AI and machine learning practitioners who aim to operationalize models within scalable data environments
- Graduates of Level 4 or equivalent technical programs wanting to build advanced technical skills in data and AI
- Professionals in cloud, DevOps, or infrastructure roles who need to align data engineering practices with enterprise solutions
This qualification is particularly valuable for those working in sectors where high-volume data processing, cloud technologies, and AI integration are critical — such as finance, healthcare, e-commerce, logistics, telecommunications, and government.