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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