Senior Data Engineer

Are you ready to be part of a transformational journey that will reshape the digital landscape of Africa? A leading Pan-African telecommunications company is launching a groundbreaking Software Engineering Centre of Excellence (COE); dedicated to building future-focused digital products designed to empower and revolutionize the continent. This is your opportunity to join an innovative team and grow your career at the forefront of technological advancement, as we accelerate towards a brighter, more connected future for Africa.  

Purpose:  

We are seeking an experienced and highly skilled Senior Data Engineer to join our team. The ideal candidate will have a robust background in data science and engineering, a proven track record of working with large datasets, and the ability to lead projects and mentor junior team members 

Key Responsibilities: 

Data Analysis and Interpretation: 

Analyze and interpret complex datasets to uncover trends, patterns, and actionable insights. 

Develop and implement advanced statistical models to solve business problems. 

Data Engineering: 

Design, develop, and maintain scalable data pipelines and architectures. 

Ensure data quality, integrity, and security across various sources. 

Optimize data storage solutions for efficiency and performance. 

Project Leadership: 

Lead data engineering projects from conception to deployment. 

Coordinate with cross-functional teams, including product, engineering, and business stakeholders, to ensure successful project delivery. 

Define project scope, goals, and deliverables that support business objectives. 

Mentorship and Collaboration: 

Mentor and provide guidance to junior data engineers. 

Foster a collaborative and innovative team environment. 

Communicate complex technical concepts and insights to non-technical stakeholders. 

Research and Development: 

Stay current with the latest advancements in data engineering.

Experiment with new tools, techniques, and technologies to continuously improve data processes and analytics. 

Deployment and Maintenance: 

Deploy and monitor data pipelines in production environments. 

Continuously improve and maintain existing data models and infrastructure. 

Implement best practices for model management and version control.