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DFSAfrica Tech Stack

Investment platform connecting African businesses to global capital

Financial Services London, london 11–50 employees Founded 2016 Partnership

DFSAfrica operates a financial platform linking African projects and enterprises to international funding sources. The tech stack spans full-stack web (C#, ASP.NET, React) alongside data infrastructure (Python, R, Hadoop, Hive, SQL, MongoDB), indicating a dual focus on user-facing transaction flows and backend analytics. Internal pain points center on sales expansion and modeling workflows at scale — both hiring signals and technical challenges that suggest the platform is transitioning from MVP to production operations.

Tech Stack 17 technologies

Core StackC# ASP.NET MySQL MongoDB Python Scala Hadoop C++ Java JavaScript React Redux SQL R Hive HTML CSS

What DFSAfrica Is Building

◆Challenges

Expanding sales and distribution team
Identifying new business opportunities
Inventory and order fulfillment
Implementing models on big data

▲Active Projects

Connective the dots initiative
Africa to the world

Hiring Activity

Minimal6 roles · 0 in 30d

Department

Data

1

Design

1

Engineering

1

Finance

1

Research

1

Sales

1

Seniority

Manager

3

Senior

2

Junior

1

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About DFSAfrica

DFSAfrica is a London-based investment platform founded in 2016 that matches African businesses and projects with capital sources globally. The company operates as a partnership with a lean 11–50 person team distributed across engineering, data, design, research, sales, and finance functions. Current initiatives focus on connectivity (connective the dots) and geographic reach (africa to the world), reflecting a market development approach. Revenue model and exact asset class focus are not publicly disclosed.

HeadquartersLondon, london

Company Size11–50 employees

Founded2016

Hiring MarketsUnited Kingdom

Frequently Asked Questions

What tech stack does DFSAfrica use?

DFSAfrica runs C#, ASP.NET, React, and Redux on the front end; SQL, MySQL, and MongoDB for persistence; and Python, R, Hadoop, and Hive for data processing and analytics.