Data Engineer - Abuja, Nigeria

QED.ai

Remote

Company Description QED.ai is a mission-driven technology company that builds data systems and AI solutions for health and agriculture, focusing on humanitarian projects aligned with SDGs 2, 3, 6, and 15. The organization partners with stakeholders in East Africa, South Asia, and other regions to help them better collect, manage, and analyze data for evidence-based policy and program decisions. QED.ai’s work emphasizes adapting technology to real-world conditions, ensuring that data tools fit the operational needs of organizations on the ground. Since its inception, the company has supported mission-critical initiatives in countries including Kenya, Tanzania, Uganda, Ethiopia, Nigeria, South Africa, Nepal, India, Taiwan, and Mexico. Team members contribute to projects with tangible social impact, particularly in low-resource and emerging contexts.
Role Description The Data Engineer will work full time on-site in Abuja, Nigeria, designing, building, and maintaining data pipelines and infrastructure to support health and agriculture projects. Day-to-day tasks include developing robust ETL processes, implementing data models and warehouses, and integrating data from multiple sources into scalable, reliable systems. The role involves close collaboration with data scientists, analysts, and project stakeholders to understand data requirements, optimize data flows, and ensure data quality and security. The Data Engineer will also monitor system performance, troubleshoot issues, and contribute to continuous improvement of the data stack and engineering best practices. This position requires a practical, detail-oriented approach to delivering reliable data solutions that support real-world decision-making.
Qualifications

Candidates should possess strong Data Engineering skills, including experience building and maintaining data pipelines and data infrastructure.
Candidates should possess Data Modeling and Data Warehousing skills to design efficient schemas and storage solutions for analytical workloads.
Candidates should possess Extract Transform Load (ETL) skills, including developing, scheduling, and optimizing ETL workflows across diverse data sources.
Candidates should possess Data Analytics skills to support reporting, dashboards, and insight generation from complex datasets.
Proficiency in SQL and at least one programming language commonly used in data engineering (e.g., Python, Java, or Scala).
Experience with relational and NoSQL databases, and familiarity with modern data platforms or cloud services (e.g., AWS, GCP, Azure) is beneficial.
Knowledge of data integration tools, workflow orchestration frameworks (e.g., Airflow, Prefect), and version control (e.g., Git) is an advantage.
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience.
Ability to work collaboratively with multidisciplinary teams, communicate technical concepts clearly, and adapt to changing project needs