The demand for people who can work with data continues to grow as businesses increasingly depend on technology, databases and digital systems to operate efficiently. For graduates who are interested in programming, databases, cloud technology and solving technical problems, starting a career in data engineering can open the door to a wide range of opportunities in the technology industry.

The Data Engineering Intern opportunity at GBS, within the Cubix division in Durban, KwaZulu-Natal, provides an opportunity for qualifying young South Africans to gain practical workplace experience in the data engineering environment.

The programme is structured as a 12-month paid internship and is intended to expose the successful intern to real-world data environments, enterprise data, data pipelines, data quality and modern technology practices.

This makes the opportunity particularly relevant to graduates who have studied Computer Science, Information Systems, Data Science, Engineering, Mathematics or a related field.

Data engineering is an important part of the modern technology ecosystem. While data analysts and Business Intelligence professionals use data to produce insights, data engineers are often responsible for helping ensure that the data is collected, moved, transformed, stored and made available in a reliable way.

For a graduate who enjoys technology but also likes problem-solving and working with information, this internship could provide a valuable foundation for a long-term career in data engineering.

About the GBS/Cubix Data Engineering Internship

The Data Engineering Intern position is offered by GBS within its Cubix division and is based in Durban, KwaZulu-Natal.

Cubix describes its internship programme as an environment where interns can learn, grow, collaborate and gain practical workplace exposure.

The Data Engineering Intern will work alongside experienced Data Engineers and Analytics professionals.

The role provides exposure to data associated with areas such as:

• Sales
• Customers
• Lead management
• Operations
• Contact centre activities
• Enterprise data environments

The intern is expected to assist with activities that support reliable data products and business decision-making.

Another important aspect of the opportunity is exposure to Microsoft Azure, which can be particularly valuable because cloud technology is increasingly important in modern data environments.

What Does a Data Engineering Intern Do?

A Data Engineering Intern supports experienced data professionals while learning how data systems operate.

Data engineering is different from simply analysing a spreadsheet.

A data engineer may work behind the scenes to ensure that information from different systems can be collected and delivered to the people and applications that need it.

For example, a business may have customer information stored in one system, sales information in another and operational information somewhere else.

A data engineering team may help connect these sources and create processes that move and transform the information.

This can involve:

• Databases
• SQL
• Programming
• Data pipelines
• Data integration
• Data quality
• Cloud platforms
• Data storage
• Automation
• Monitoring

As an intern, you are unlikely to be expected to know everything from day one.

The purpose of the internship is to develop your practical knowledge while working alongside experienced professionals.

Understanding Data Pipelines

One of the most important concepts for aspiring data engineers to understand is the data pipeline.

A data pipeline is essentially a process through which data moves from one or more sources to a destination where it can be used.

For example:

Source → Extraction → Transformation → Storage → Reporting/Analytics

A company could receive information from customer applications, operational systems and sales platforms.

That information may need to be collected, cleaned and transformed before it can be used in a dashboard.

Data engineers help build and maintain the processes that make this possible.

Understanding this concept can help graduates appreciate why data engineering is so important.

Working With Databases

Databases are at the centre of many data engineering environments.

Businesses generate enormous quantities of information.

Instead of storing everything in ordinary documents, organisations often use database systems designed to store and retrieve information efficiently.

A Data Engineering Intern may gain exposure to database concepts such as:

• Tables
• Rows
• Columns
• Primary keys
• Relationships
• Queries
• Data types
• Indexes
• Data validation

You do not necessarily need advanced database knowledge before applying for an internship, but understanding the fundamentals can give you a strong starting point.

Why SQL Is Important

The vacancy specifically mentions a basic understanding of SQL.

SQL, or Structured Query Language, is one of the most important skills for people entering data-related careers.

SQL is used to interact with relational databases.

A beginner should understand commands such as:

• SELECT
• FROM
• WHERE
• ORDER BY
• GROUP BY
• JOIN
• COUNT
• SUM
• AVG

For example, an analyst or engineer might use SQL to retrieve information about customers, transactions or sales.

Developing good SQL skills can significantly improve your future employment prospects in data-related roles.

Exposure to Python

The vacancy also mentions programming concepts, preferably Python.

Python is widely used across the technology and data industries.

It can be used for:

• Data processing
• Automation
• Data analysis
• Scripting
• Application development
• Data engineering
• Machine learning

A graduate does not necessarily need to be an advanced Python developer for an internship.

However, learning basic Python can help you become more competitive.

Start with fundamentals such as:

• Variables
• Data types
• Lists
• Dictionaries
• Loops
• Functions
• Conditional statements
• Error handling
• Reading files

Once you understand these concepts, you can begin exploring Python libraries commonly used in data work.

Microsoft Azure and Cloud Technology

Another exciting aspect of the opportunity is exposure to Microsoft Azure.

Cloud computing has transformed the way organisations build and operate technology systems.

Instead of keeping all computing resources inside a company’s physical infrastructure, organisations can use cloud platforms to access computing, storage, databases and other services.

Azure is one of the major cloud platforms used by businesses around the world.

For an aspiring data engineer, exposure to cloud technology can be valuable because modern data environments increasingly use cloud-based infrastructure.

Even basic knowledge of concepts such as:

• Cloud storage
• Virtual machines
• Databases
• Data services
• Identity and access
• Data pipelines

can help establish a useful foundation.

Data Quality

Data engineering is not only about moving information.

The information also needs to be reliable.

Imagine a company has duplicate customer records.

Or a database contains thousands of missing values.

Or dates are stored in different formats.

If this information is sent directly to a reporting system, the resulting analysis could be inaccurate.

Data engineers therefore have an important role in maintaining data quality.

An intern may learn about:

• Data validation
• Duplicate detection
• Missing values
• Data consistency
• Error handling
• Data monitoring
• Data cleansing

This is one of the reasons why attention to detail is important in the role.

Working With Data Engineers and Analytics Professionals

The intern will work alongside experienced Data Engineers and Analytics professionals.

This provides an opportunity to understand how different technology roles work together.

A typical data environment might include:

Data Engineers who prepare and manage data.

Data Analysts who analyse data to answer business questions.

Business Intelligence Analysts who create reports and dashboards.

Data Scientists who use advanced statistical and machine-learning techniques.

Business stakeholders who use the information to make decisions.

Learning how these roles interact can help an intern decide which direction they want to pursue in the future.

Requirements for the Data Engineering Internship

Applicants must meet the eligibility requirements specified for the internship.

Candidates must:

• Be South African citizens
• Have a National Senior Certificate/Grade 12
• Have completed a relevant degree or diploma
• Be between 18 and 35 years old
• Have a clear criminal record
• Have a clear ITC record
• Not currently be employed
• Not currently be participating in another internship or learnership programme

The relevant academic fields include:

• Computer Science
• Information Systems
• Data Science
• Engineering
• Mathematics
• Related disciplines

Applicants should also have a basic understanding of databases and SQL.

Programming knowledge, particularly Python, is advantageous.

Why This Job Is Worth Applying For

1. It Provides Real Workplace Experience

One of the biggest advantages of an internship is the opportunity to move beyond theory.

You may have completed database or programming modules at university, but working with experienced professionals provides a different type of learning.

You get to see how technology is actually used in business.

2. It Is a 12-Month Programme

A longer internship can provide more opportunities to develop practical skills.

You have time to become familiar with workplace processes, systems and professional expectations.

3. It Is a Paid Internship

The programme is advertised as a paid internship.

This can make it an attractive opportunity for graduates who need workplace experience while also receiving a stipend.

4. Exposure to Cloud Technology

The opportunity includes exposure to Microsoft Azure and modern data engineering practices.

Cloud skills can be useful when applying for future technology positions.

5. Opportunity to Learn From Experienced Professionals

Working alongside Data Engineers and Analytics professionals can provide valuable practical knowledge.

Observe how they approach problems.

Ask questions.

Learn how they document their work.

Understand why systems are designed in particular ways.

6. Data Engineering Has Multiple Career Paths

Data engineering knowledge can eventually lead into several technology careers.

You could move towards:

• Data Engineering
• Cloud Engineering
• Data Analytics
• Business Intelligence
• Database Administration
• Software Development
• Data Architecture
• Data Science

Skills That Increase Your Chances of Getting Selected

SQL

SQL should be one of your top priorities.

Practise writing queries against sample databases.

Learn how to combine information from multiple tables using JOIN operations.

Python

Develop basic Python programming skills.

Practise small automation and data-processing projects.

Database Fundamentals

Understand how relational databases work.

Know the difference between tables, records, fields and relationships.

Cloud Fundamentals

Learn the basic concepts of cloud computing.

Explore introductory Azure learning material and understand the role of cloud-based data services.

Problem-Solving

Data engineering involves solving technical problems.

If a pipeline fails, the engineer needs to investigate why.

Analytical Thinking

You need to be able to break a large problem into smaller components.

Attention to Detail

A minor configuration or data error can potentially affect an entire data process.

Communication

Data engineers do not work alone.

They communicate with developers, analysts, managers and business users.

Willingness to Learn

Technology changes constantly.

A successful data professional needs to continue learning throughout their career.

Building a Data Engineering Portfolio

One of the best ways to demonstrate your interest in data engineering is by creating personal projects.

You do not need an expensive computer or corporate database.

You can create a simple project using publicly available datasets.

For example, build a small pipeline that:

1. Reads a CSV file.
2. Cleans the data using Python.
3. Stores the information in a database.
4. Uses SQL to query the database.
5. Produces a basic report.

This demonstrates several relevant skills at once.

You can then document the project on your CV.

Another Project Idea

Create a fictional sales data pipeline.

Your dataset could contain:

• Customer ID
• Product
• Region
• Sales amount
• Date
• Sales representative

Use Python to clean the data.

Load it into a database.

Use SQL to answer questions such as:

• Which product generated the most sales?
• Which region performed best?
• What was total monthly revenue?
• Which sales representative had the highest sales?

Then create a Power BI dashboard.

This project would allow you to demonstrate knowledge across data engineering, SQL, analytics and visualisation.

Career Growth Opportunities

A Data Engineering Intern can potentially progress through several stages.

Junior Data Engineer

After gaining sufficient experience, a candidate may move into a Junior Data Engineer position.

The role may involve maintaining pipelines, writing SQL, supporting databases and assisting with data integration.

Data Engineer

With additional experience, you can become responsible for more complex data pipelines and systems.

Senior Data Engineer

Senior Data Engineers typically handle complex technical problems and may help design data architecture.

Cloud Data Engineer

With strong Azure or other cloud-platform skills, you could specialise in cloud data engineering.

Data Architect

Experienced professionals can eventually move into architecture roles involving the design of large-scale data environments.

Data Platform Engineer

This pathway focuses on building and maintaining platforms that allow organisations to process and access data.

Analytics Engineer

An Analytics Engineer sits between traditional data engineering and analytics, helping transform data into structures that analysts and business users can work with.

How to Prepare for the Interview

Research GBS and Cubix

Before your interview, learn about the organisation and the Cubix environment.

Understand the type of technology and business environment in which you could be working.

Revise SQL

Do not ignore SQL.

Practise basic queries before the interview.

Make sure you understand SELECT, WHERE, JOIN, GROUP BY and aggregate functions.

Revise Python Fundamentals

If Python appears on your CV, be prepared to discuss what you know.

You may be asked to explain a simple piece of code or describe a project.

Learn Data Pipeline Concepts

Be able to explain what a data pipeline is in simple language.

Research Azure

Learn basic cloud concepts and familiarise yourself with Azure’s role in enterprise technology.

Prepare Examples

Prepare examples showing how you have:

• Solved a difficult problem
• Worked with a team
• Learned a new technology
• Completed a project
• Found and corrected an error
• Managed a deadline

These examples can come from university, college or personal projects.

Possible Interview Questions

Why do you want to become a Data Engineer?

Explain your interest in technology, data and problem-solving.

What is a database?

Give a simple explanation of a structured system used to store and manage information.

What is SQL?

Explain that SQL is a language used to interact with relational databases.

What is a data pipeline?

Explain how data can be collected from sources, processed or transformed and delivered to a destination for storage, reporting or analysis.

Why is data quality important?

Explain that poor-quality data can result in unreliable analysis and poor business decisions.

What programming language do you know?

If you know Python, explain your level honestly.

What is cloud computing?

Give a simple explanation of accessing computing resources and services through cloud infrastructure rather than relying solely on local systems.

Have you worked on a data project?

Use a university or personal project.

If you have no formal experience, do not simply answer “no.”

Explain relevant academic or personal projects you have completed.

How to Answer When You Do Not Know Something

Internship interviews are not necessarily designed to test whether you already know everything.

If you do not know an answer, avoid making something up.

Instead, explain what you know and show your willingness to learn.

For example:

“I have not worked with that technology directly yet, but I understand the underlying concept and I am currently learning more about it.”

This is generally stronger than pretending to have experience you do not possess.

Salary Expectations

The vacancy describes the opportunity as a 12-month paid internship, but the advertisement does not provide a specific monthly stipend.

Candidates should therefore confirm the stipend with the employer during the recruitment process.

It is important not to confuse an internship stipend with the salary of a permanent Data Engineer.

Once professionals move into permanent positions, earnings can increase substantially depending on:

• Technical skills
• Experience
• Qualifications
• Cloud certifications
• Programming ability
• SQL expertise
• Employer
• Industry
• Seniority
• Location

Data Engineering is generally considered a specialised technology field, and professionals with strong cloud, programming and database skills can become highly competitive in the job market.

For an intern, however, the immediate objective should be to develop practical skills and build experience that can support future permanent employment.

Similar Jobs to Search For

If you are interested in this opportunity, do not search only for “Data Engineering Intern.”

Other useful search terms include:

• Data Engineer Intern
• Junior Data Engineer
• Data Analyst Intern
• Business Intelligence Intern
• Database Intern
• SQL Intern
• Cloud Intern
• Azure Intern
• Data Science Intern
• IT Graduate Programme
• Technology Graduate Programme
• Junior BI Analyst
• Analytics Intern
• Database Administrator Intern
• Software Developer Intern
• Data Platform Intern
• Cloud Data Engineer
• Graduate Data Engineer
• Data Engineering Graduate Programme

Different companies use different job titles for similar entry-level opportunities.

How to Make Your CV Stand Out

Your CV should clearly show your qualification and relevant technical skills.

A useful technical skills section could include:

Technical Skills

• SQL
• Python
• Database fundamentals
• Microsoft Azure
• Data processing
• Data analysis
• Microsoft Excel
• Power BI

Only include skills you genuinely possess.

If your knowledge is at beginner level, do not describe yourself as an expert.

You can also include projects.

For example:

Student Data Pipeline Project

Created a basic data pipeline using Python and SQL to clean, process and analyse a sample dataset.

This provides evidence that you have applied your knowledge.

Certifications Can Help

Although certifications are not necessarily required for an internship, additional learning can strengthen your long-term profile.

You can explore introductory certifications and learning programmes in areas such as:

• Azure
• SQL
• Python
• Data Engineering
• Cloud Computing
• Power BI

Do not collect certifications simply for the sake of having certificates.

Make sure you actually understand the technology you are studying.

The Importance of Continuous Learning

Data engineering is not a career where learning stops after university.

Technology changes quickly.

Cloud platforms introduce new services.

Data architectures evolve.

Programming tools change.

Businesses adopt new approaches to data management.

A successful data engineer therefore needs to remain curious.

Use your internship as an opportunity to learn from experienced colleagues and understand how enterprise systems operate.

Mistakes to Avoid During the Internship

If you are selected, remember that the internship is also an extended opportunity to demonstrate your professionalism.

Avoid:

• Arriving late
• Ignoring instructions
• Hiding mistakes
• Sharing confidential information
• Refusing to ask questions
• Pretending to understand something you do not understand
• Failing to document your work
• Ignoring feedback

Instead:

• Ask sensible questions
• Take notes
• Learn from mistakes
• Communicate problems early
• Document your work
• Volunteer for learning opportunities
• Improve your technical skills

Final Thoughts

The Data Engineering Intern opportunity at GBS/Cubix in Durban can provide an important entry point for graduates who want to establish careers in data and technology.

The internship is particularly relevant to candidates who have completed qualifications in Computer Science, Information Systems, Data Science, Engineering, Mathematics or related fields.

The role provides exposure to important areas such as databases, SQL, programming, data engineering practices, data quality, enterprise data and Microsoft Azure.

For graduates entering a competitive technology job market, gaining practical experience can be extremely valuable.

However, applicants should not stop learning after submitting their application.

Use the opportunity to strengthen your SQL skills.

Learn Python.

Explore Microsoft Azure.

Understand databases.

Build personal projects.

Create a portfolio.

Learn how data pipelines work.

Most importantly, develop the habit of solving problems logically.

A successful Data Engineer needs more than programming knowledge. They need to understand how data moves through an organisation, how to maintain its quality and how to build reliable systems that allow other professionals to use that information.

The internship can also serve as a foundation for several future careers. With experience, the successful candidate could potentially progress towards positions such as Junior Data Engineer, Data Engineer, Senior Data Engineer, Cloud Data Engineer, Data Platform Engineer, Analytics Engineer or Data Architect.

For a young graduate looking to enter the technology industry, an opportunity to work alongside experienced data professionals and gain practical exposure to enterprise data can be a significant career-building step.

If you meet the eligibility requirements and have a genuine interest in data, programming, databases and cloud technology, this is the kind of internship that can help turn your academic qualification into practical industry experience.