Moniepoint is a financial technology company digitising Africa’s real economy by building a financial ecosystem for businesses, providing them with all the payment, banking, credit and business management tools they need to succeed.
About the role :
- At Moniepoint, data is at the core of everything we do. We are a customer-centric company, and your work will enable our teams to make informed, data-driven decisions that directly impact the success of our business. As a Data Engineering Lead, you will help craft robust, scalable systems that support our business intelligence and data-driven operations. We value leaders who are not only technically adept but also excited about mentoring others and pushing the boundaries of what's possible with data.
What you will get to do
- Build and maintain robust data pipelines processing large volumes of data
- Analysis of large data sets using tools such as Python & SQL
- Update and optimize our data platform for speed, scalability and cost
- Coordinate with different functional teams to understand and meet their data needs
- Develop processes and tools to monitor and analyze model performance and data accuracy
- Solve general data-related problems
- Setting up new pipelines for the full stream/enrichment/curation process
- Upkeep of source code locations
- Investigating and utilising ML & AI to improve the cloud offering
- Development of junior staff members
To succeed in this role, you should have
- Proven experience as a Data Engineer (5+ years, can be made up for with accomplishments)
- Strong problem solving skills
- Advanced proficiency with SQL
- Proficiency with Python
- Experience with cloud platforms (e.g. Google Cloud, AWS, Azure)
- Experience using version control tools such as git
- Excellent written and verbal communication skills
- A drive to learn and master new technologies and techniques
- A bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or any other related field
Experience with the following would be a plus
- Data governance
- Building and deploying machine learning models
- Terraform or other infrastructure as code tools
Method of Application
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