ICTQual AB Level 5 Diploma in Data and AI-Data Engineer

The ICTQual AB Level 5 Diploma in Data and AI – Data Engineer is a dynamic qualification tailored to prepare learners for the technical demands of designing, building, and maintaining modern data infrastructures. With a structured curriculum grounded in real-world applications, this Level 5 diploma equips learners to support analytics and AI initiatives with robust, scalable data systems.

Learners will develop key skills in constructing reliable ETL/ELT pipelines, integrating diverse data sources, and optimising data architectures—including relational databases and data warehouses. The course emphasises hands-on training with SQL, Python, and industry-standard workflows, alongside best practices for data modelling, quality control, and ethical AI deployment.

Graduates emerge well-positioned for roles such as Data Engineer, Cloud Data Developer, or ETL Specialist, capable of enabling seamless data flow and access across business operations. Whether aiming to elevate operational efficiency, drive innovation, or support advanced analytics, this qualification offers a powerful blend of technical proficiency and strategic insight for modern data-driven environments.

Course overview

Level 5 Diploma in Data and AI-Data Engineer

To enrol in ICTQual AB Level 5 Diploma in Data and AI-Data Engineer, learner must meet the following entry requirements:

  • Age Requirement: Learners must be 18 years or older at the time of enrolment..
  • Educational Background: A Level 4 qualification in data, computing, software, or a related discipline is recommended. Equivalent industry experience in data processing or IT infrastructure may also be considered.
  • Digital Skills: Learners must be confident in using digital tools, data systems, and online learning platforms.
  • English Language Proficiency: Learners should have a strong command of written and spoken English. Non-native speakers are advised to hold an English qualification equivalent to CEFR Level B2.
  • Programming & Technical Skills: Familiarity with Python, SQL, or other scripting languages is highly beneficial. Learners should also understand basic data structures and databases.

This qualification, the ICTQual AB Level 5 Diploma in Data and AI-Data Engineer, consists of 6 mandatory units.

  1. Designing and Managing Data Pipelines
  2. Relational and NoSQL Database Architecture
  3. Data Storage, Warehousing & Cloud Integration
  4. ETL/ELT Processing and Automation Tools
  5. Data Quality, Governance & Security
  6. Scalable AI Infrastructure & Performance Optimisation

Learning Outcomes for the Study Units:

1. Designing and Managing Data Pipelines

  • Design efficient and reliable data pipelines tailored for ingestion, transformation, and loading of diverse data sources.
  • Monitor pipeline performance, troubleshoot issues, and implement corrective actions to maintain data flow integrity.
  • Employ tools and technologies (e.g., scheduling frameworks or orchestration platforms) to ensure automation and robustness.

2. Relational and NoSQL Database Architecture

  • Evaluate and compare database architectures, selecting appropriate relational or NoSQL models based on use case and data complexity.
  • Craft efficient schema designs that support scalable storage and query performance.
  • Apply indexing, partitioning, and query optimisation techniques to enhance data retrieval and operational efficiency.

3. Data Storage, Warehousing & Cloud Integration

  • Architect and implement data storage solutions—including warehouses and data lakes—that support organisational analytics needs.
  • Integrate cloud-based storage platforms, applying best practices for scalability, availability, and resilience.
  • Evaluate storage strategies for cost, performance, and long-term manageability.

4. ETL/ELT Processing and Automation Tools

  • Build and automate ETL/ELT workflows using tools or scripts to manage large-scale data processing tasks.
  • Ensure data transformations are accurate, efficient, and repeatable for high-throughput environments.
  • Monitor task runtime and use automation frameworks to detect failures and optimise resource utilisation.

5. Data Quality, Governance & Security

  • Implement data validation, cleansing, and quality assurance workflows to ensure trustworthiness of datasets.
  • Apply governance frameworks and security protocols—including encryption, access control, and audit logging—to safeguard data assets.
  • Ensure compliance with data protection standards and organisational policies across engineering workflows.

6. Scalable AI Infrastructure & Performance Optimisation

  • Architect infrastructure that supports scalable AI and machine learning workloads—leveraging cloud services, parallel processing, and containerisation.
  • Tune system performance by optimising hardware or resource configurations, caching, and concurrency.
  • Evaluate and enhance infrastructure efficiency to support AI-driven data processing at scale.

The ICTQual AB Level 5 Diploma in Data and AI – Data Engineer is a career-focused qualification that opens the door to advanced academic opportunities and highly skilled roles in modern data infrastructure. Upon completion, learners gain the technical and strategic foundation to thrive in data engineering and AI-driven environments.

Academic Progression Opportunities

Learners can advance to:

  • Level 6 Diplomas in Data Science, Artificial Intelligence, or Advanced Computing
  • Professional certifications including:
    • Microsoft Azure Data Engineer Associate
    • Google Cloud Certified Data Engineer
    • AWS Certified Data Analytics

Career Advancement Opportunities

Graduates of this diploma are qualified for specialist and senior technical roles, including:

  • Data Engineer
  • ETL Developer
  • Cloud Data Integration Specialist
  • AI Infrastructure Developer
  • Data Platform Administrator
  • Big Data Operations Analyst

These roles are in high demand across industries such as finance, health tech, retail, government, education, and logistics.

Professional Competencies Developed

  • Advanced data pipeline design and management
  • Scalable database and cloud infrastructure development
  • ETL/ELT automation and optimisation
  • Data security, quality assurance, and AI-ready system design

FAQs

The course is ideal for individuals with a background in data analytics, computing, software development, or IT who want to progress into data engineering roles. It’s also suitable for professionals aiming to upskill in cloud, automation, and AI infrastructure.

Learners must be at least 14 years old with basic English and digital skills. No formal qualifications are necessary.

ICTQual AB Level 5 Diploma in Data and AI-Data Engineer is 50 Credits training program. As this Training program have mandatory assessment which will be conducted through Approved Training Centers.

ICTQual AB allows to offer Level 5 Diploma in Data and AI-Data Engineer in various formats, including online, in-person, or a combination of both. Participants can choose the format that best fits their schedule and learning preferences. But final decision is made by ATC.

Yes, ICTQual AB Level 5 Diploma in Data and AI-Data Engineer consist of 6 mandatory assessments . These assessments are designed to evaluate participants’ comprehension of course material and their capacity to apply concepts in practical situations. It is mandatory to pass assessments with a minimum score of 75%