Overview

Specialise in Data Engineering and become an Azure-certified Data Engineer

Data Engineers are the architects and builders of the data foundation upon which modern businesses thrive. Without reliable, scalable data pipelines, the work of Data Analysts to uncover insights and ML Engineers to build powerful AI models simply cannot exist. The rapid advancements in AI, in particular, are further accelerating the demand for robust data infrastructure, making the Data Engineer’s role even more pivotal. Despite these high organizational data needs, skilled Data Engineers remain a scarce and highly sought-after talent on the local market. Specialising now means securing a critical, high-impact career at the forefront of the data revolution.

Our 12-week part-time program delivers a rigorous, hands-on learning experience. It aligns closely with the demands of the Microsoft Azure Data Engineering certification, moving you from theory to practical application. You will build real-world data pipelines and solutions, focusing on Big Data Architectures, Distributed Processing (Apache Spark), Workflow Orchestration (Apache Airflow), Cloud Data Services (Microsoft Azure), and Containerisation (Docker). The curriculum also covers advanced topics like data lakehouses and AI-powered data engineering.

This specialisation course is ideal for ambitious professionals ready to elevate their technical skills. It’s designed for Data Scientists looking to productionise models, Data Analysts aiming to build foundational data systems, and Developers keen on expanding into large-scale data system engineering.

Prerequisites: To thrive in this intensive program, you should be comfortable with at least one programming language (preferably Python) and possess a solid grasp of SQL. Basic command-line proficiency is also essential.

Curriculum

What you’ll learn in our Data Engineering Program

Curated from our in-depth research and experience of the most in-demand skills for Data engineering career pathways, our curriculum is broken down into 12 weeks encompassing the following:

This program has prerequisites: you should already be a developer, data scientist, or data analyst comfortable with at least one programming language such as Python and possess a solid grasp of SQL. The course builds on your existing skills to specialise in Data Engineering.

This foundational module sets the stage for your journey into modern data infrastructure. You’ll explore essential principles, tools, and architectures that power data-driven systems at scale, understanding why traditional systems fall short for “big data.”

  • Core Concepts: Role of a Data Engineer, ETL principles, and the definition of Big Data
  • Big Data Architectures: Key components for storage, processing, and orchestration
  • Data Governance: Essentials of data security, lineage, and quality in scalable systems
  • Scalable Storage & Access: Exploring solutions for massive datasets and data retrieval methods
  • Real-time Data Flows: Understanding message brokers and foundational streaming data concepts

Dive deep into the core technologies for managing and automating large-scale data workflows. This module equips you with practical skills to process massive datasets efficiently using Spark and build resilient, scheduled pipelines with Airflow.

  • Apache Spark Fundamentals: Architecture, data processing, and optimisation techniques
  • PySpark for Data Engineering: Performing scalable transformations with DataFrames and RDDs
  • Apache Airflow Essentials: Building, scheduling, and scaling complex data workflows (DAGs)
  • Pipeline Automation: Automating data tasks for reliable and efficient operations
  • Data Quality in Distributed Systems: Implementing validation and cleansing within Spark pipelines

Master the deployment, management, and optimisation of data engineering solutions. This module introduces you to containerisation with Docker for portable environments, alongside advanced topics in data architecture and performance.

  • Docker for Data Engineering: Fundamentals of containerisation and image management
  • Container Orchestration: Using Docker Compose for multi-container application definitions
  • Data Persistence with Docker: Managing data across container restarts using volumes
  • Query Optimization: Techniques for improving performance in SQL and Spark
  • Advanced Data Architectures: Best practices for scaling workflows, data partitioning, and Data Lakehouses (e.g., Delta Lake)

Explore the cutting edge of data engineering and prepare for industry certification. This forward-looking module covers how AI is reshaping data practices, integrates modern MLOps/DataOps principles, and provides focused preparation for Azure Data Engineering certification.

  • AI in Data Engineering: Automating pipelines and enhancing data quality with machine learning
  • DataOps & MLOps Integration: Seamlessly managing data and machine learning operations
  • Generative AI for Development: Accelerating coding and problem-solving with AI tools
  • Future Trends: Insights into the evolving landscape of data engineering
  • Azure Certification Prep: Focused sessions for the Microsoft Azure Data Engineering certification

To graduate the program, students are required to complete a comprehensive, end-to-end data engineering capstone project. This involves designing and implementing a complete data pipeline – from ingesting, processing, and orchestrating, to storing big data – utilising the tools and techniques covered throughout the course. This capstone experience solidifies your technical skills and prepares you with real-world readiness for complex data challenges.

Zindua your career in tech. Join our Data Engineering program today!

Apply Now

Testimonial

Hear from a graduate

Mercy Samoei, data science program graduate in 2023

If I compare the person I am now, versus the person I was prior to joining Zindua, I would say that I have grown in more than one aspect. Zindua has been a good learning experience: amazing tutors, the students you get to interact with, and it is also quite time friendly. Classes are usually sizeable enough so it is easy to have a one-on-one experience, not like the normal classroom experience you get from uni. What I love most about Zindua is the personalised learning approach, blended learning, where some classes are online and others in-person. They also have a very favourable income-share agreement financing.

Mercy Samoei, Data Science Graduate

Your Zindua experience runs from admissions to placement

1

Complete application

Takes less than 2 minutes to complete. Choose your program and expected start date.

2

15-minute interview

The interview allows us to make sure your background aligns with your chosen program.

3

Pay enrolment deposit

Confirm your enrolment by paying a KES 5K deposit, deductible from your actual fees.

1

Personalised Learning

We pride ourselves in very small classes, allowing you as much touch with your technical mentor.

2

Project-based approach

You’ll work on a short daily challenge on weekdays, weekly project, and capstone after each module.

3

Global cloud certification

Curriculums are modelled on certification exams by Microsoft Azure and AWS.

1

Career Development

Beyond classes, we have a module focused on CVs, LinkedIn, portfolios, and technical interviews.

2

Job Placement Support

We don’t offer job guarantees but we connect some of our graduates to our employer networks.

3

Life-long engament

As an alumni, you’ll have free access to our masterclasses and placement support on a need-basis.

Zindua your career in tech. Join our Data Engineering program today!

Apply Now

financing

Choose the pricing options that fits your needs

We champion flexible financing options to improve the accessibility of our programs:

One-Time Upfront Payment

Pay KES 75K one-time fee (This is the cheapest financing option)

Pay in TWO Instalments

Pay KES 39K every 6 weeks for 2 total instalments; totals to KES 78K.

Flexi Payment Plan (Lipa Mdogo Mdogo)

Pay KES 13,750 monthly for 7 months. This financing will require the student/parent (whoever will be making payments) to go through a credit vetting process by Chaptr Global. This option is ideal for students who cannot afford the stipulated upfront fee or instalment pricing options.

Income-Share Agreement (Learn now, pay later)

Pay 50% of tuition fees and defer the rest into an income-share agreement. You’ll pay KES 20K every month for 2 monthly instalments. Once you graduate, you’ll be required to pay 10% of your earned income for 12 months. If you do not get a job you pay nothing! This financing plan is ONLY available to students with Bachelor’s Degree or in their final year of university i.e. students who’ll be looking for employment immediately they graduate Zindua School.

*Note: The cost of the associated certification exam has been included. Graduate with a Microsoft Azure global certification.

Frequently asked questions

We have a three-step admissions process. Apply on website, attend a 15-minute interview, and pay the enrolment deposit to confirm your enrolment. Simple and straightforward. Since there could be some weeks between the time you pay the deposit and the orientation program, you’ll be invited to our Free Courses to start learning concepts that would be beneficial for your learning journey.

Yes, Zindua School has an enrolment deposit of KES 5,000 which is deductible from your program fees. The deposit allows us to confirm your slot in an upcoming intake. Fees will be paid (minus the deposit) once you have started the program.

Zindua School is extremely practical and our focus is on preparing our students for real-world problems in today’s job market. Most of our graduates get hired on the basis of their portfolio and this speaks to the quality of the skills you’ll gain at Zindua School.

Unfortunately, we do NOT offer a job guarantee. However, we do offer job placement support for graduates. This involves our career module where you’ll optimise your CV/resume, LinkedIn profile, portfolio, and even learn about technical interviews. Additionally, we do connect some of our graduates to our constantly growing employer networks.

For our full-time program, you’ll be expected to attend classes in-person on three weekdays and online on two weekdays. Classes run from 9am to 2pm, with take home coding assignments on each day. You are required to commit 35-40 hours weekly if you plan to join us full-time.

For our part-time program, you’ll be expected to attend online classes in the evening from Monday to Thursday. The online classes run for two hours and are slotted anytime from 6pm to 10pm based on your class group. You’ll have in-person classes on Saturdays from 10am to 2pm. You are required to commit 20-25 hours weekly to cover for class sessions and out-of-class projects. This is ideal for those with work or school commitments.

Note: full-time programs are shorter than the part-time program as there is more time committed per week for learning. However, both programs cover the same content and have the same expected outcomes.

Our ISA allows you to pay 50% of the program and pay the rest once you start earning through an income-share. When you are not earning, you pay nothing.This financing plan is only open to learners who are in their final year of university or already have a diploma or Bachelor’s Degree. This financing plan only applies to our core programs and specialisation programs; NOT lite core programs (Data Analytics and Web Development) or our short courses (Product Management and Data Structures Algorithms)