Senior Data Engineer
Moniepoint
- Data Engineer
- Remote
- 5+ years
At a glance
About the company
Moniepoint describes itself as Africa's all-in-one financial platform, with payments, banking, credit and business tools. About 20 million businesses and individuals use it every month. It is Nigeria's largest merchant acquirer, and its subsidiaries process over $250 billion in digital payments a year.
Description
You build and look after the data platform behind a large payments business. You will:
- Build and maintain pipelines that handle large volumes of data
- Make the data platform faster, easier to scale and cheaper to run
- Work with other teams to understand and meet their data needs
- Create tools and processes that watch data accuracy and model performance
- Solve day-to-day data problems as they come up
Qualifications & Skills
Must have 6
- 5+ years working as a data engineer
- Advanced SQL and Python
- Experience with a cloud platform such as Google Cloud, AWS or Azure
- Version control with Git
- Strong problem-solving, and clear written and spoken communication
- A degree in computer science, statistics, mathematics, engineering or a related field
Nice to have 3
- Data governance experience
- Built and deployed machine learning models
- Terraform or another infrastructure-as-code tool
How to stand out for this job
Written by our team from the employer's post. Work through it in order, then apply.
1What they actually want
Our plain-words read of this job. It explains the job, not the employer's own words.
This is a hands-on engineering job on a very large payments platform. Moniepoint moves huge amounts of transaction data every day, and other teams depend on it arriving complete and on time. Your week is spent building and fixing pipelines, and tuning the platform so it runs faster and costs less. You also add checks that catch bad data early. When a team needs new data, you work out what they need and build it.
Because the role is remote and senior, they want a data engineer with five or more years who needs little supervision. Strong SQL and Python are essential, and so are cloud experience and Git. The process starts with a take-home task, so that is your first chance to show clean, tested code. To stand out, point to a pipeline you built at scale and say what it saved in time or money.
2Words to use in your CV
Use the words that are true for you. The dark ones matter most for this job.
- data pipelines
- SQL
- Python
- Google Cloud / AWS / Azure
- Git
- scalability
- cost optimisation
- data quality monitoring
- large-scale data
- ETL/ELT
- cross-functional teams
- Terraform
- data governance
4Tailor your portfolio
Make a copy of your portfolio for this job and lead with these three projects. Give the problem, the data, the tools and the result as a number.
- 01
An end-to-end pipeline
Load a public data set into a cloud warehouse on a schedule, with the code on GitHub.
- 02
A data-check layer
Tests that stop a load when rows are missing, duplicated or late.
- 03
Infrastructure as code
A small Terraform setup that creates the storage and jobs your pipeline needs.
3Tailor your CV
- Headline“Senior Data Engineer | Python, SQL, Cloud Data Pipelines”
- SummaryOpen with your years as a data engineer, your cloud platform and the data volumes you handle.
- OrderPut pipeline and platform work first. Move dashboard or analysis work lower.
- Show scale and costGive the data volume you moved and any speed or cost saving.
- Show monitoringOne bullet on the checks or alerts you built to catch bad data.
BeforeWorked on ETL pipelines.
AfterRebuilt 15 daily pipelines in Python on Google Cloud, handling 200 million rows a day and cutting compute cost by 30%.
Example only. Use your own real numbers.
5Learn the missing skill
SQL and Python for Data Analysis
Live cohort · Starts 4 Nov 2026
₦200,000 or 4 × ₦50,000
6Before you apply
Apply on Moniepoint's careers page
You'll leave Exalda. Your application goes straight to the employer, and we never charge you to apply.
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