Data Engineering landscape in Kenya
Data engineering has become one of the most important technical roles in modern organizations. Every company wants dashboards, AI models, automated reports, customer insights, fraud detection, credit scoring, logistics optimization, and real-time monitoring. But behind all these solutions is one key person: the data engineer.
In Kenya, the demand for data engineers is growing across banks, fintechs, insurance companies, telecoms, health-tech startups, NGOs, logistics companies, government-linked digital projects, and international organizations. Companies are no longer just looking for someone who can write SQL queries. They want someone who can design reliable data pipelines, clean messy data, manage databases, work with cloud tools, automate workflows, and support analytics and machine learning teams.
Preparing for a technical data engineer interview therefore requires more than memorizing definitions. You need to understand the role deeply, practise real technical problems, build projects, and be able to explain your thinking clearly.
This article breaks down how to prepare for a data engineering interview, especially if you are applying in the Kenyan job market.
Steps by step guidance
1. Understand the Role Clearly
Before the interview, understand what a data engineer actually does.
Common responsibilities include:
Building ETL and ELT pipelines
Designing databases and data warehouses
Ensuring data quality and security
Automating reports and workflows
Supporting dashboards and machine learning teams
Cleaning and transforming data
Connecting to APIs
Monitoring failed pipelines
In Kenya, many companies are still moving from manual Excel reporting to automated data systems. This means employers value candidates who can solve practical problems, not just explain theory.
2. Master SQL
SQL is one of the most important skills in a data engineering interview.You need to understand your logic clearly because interviewers want to know how you think as well.
Practise with questions such as:
For example, finding duplicate customers
SELECT
customer_id,
SUM(amount) AS total_amount
FROM transactions
GROUP BY total_amount
ORDER BY total_amount DESC
LIMIT 5;
3. Learn Python for Data Engineering
Python is commonly used for automation, API integration, file processing, and data cleaning.
Focus on python libraries such as pandas, requests, and error handling.
For example; importing pandas libraries
import pandas as pd
import requests
4. Prepare for Cloud and Pipeline Tools
Many Kenyan companies are adopting cloud tools, especially AWS, Azure, and Google Cloud.
Also learn pipeline and orchestration tools such as airflow, dbt, prefect.
A good answer to a cloud pipeline question may be:
"I would extract data from the source API, store the raw data in cloud storage, validate and transform it, load it into a warehouse, and add monitoring to alert the team when the pipeline fails."
Here is an flowchart to help you understand various areas to prepare for an interview as a data engineer.
To understand how to land a data analyst role, kindly check the article below;
How to land a data analyst role in 6 months
Conclusion
Many organizations need people who can move them from manual reporting to automated, reliable, and scalable data systems. Do not just memorize definitions. Build projects, explain your thinking, practise real interview questions, and show how your skills solve business problems. A strong data engineer is not just someone who moves data. A strong data engineer builds systems that businesses can trust.
