About the job
About One Acre Fund
Established in 2006, One Acre Fund empowers over 5.5 million smallholder farmers to enhance their agricultural productivity. Operating across nine countries that host two-thirds of Africa's farming population, we provide top-notch farming supplies, tree seedlings, accessible credit, modern agricultural training, and a variety of other essential agricultural services. Our model typically enables farmers to boost their income and assets on supported land by more than 35 percent while significantly enhancing their resilience. This achievement is driven by our dedicated team of over 9,000 full-time staff, representing diverse backgrounds and professions. To discover more about our workplace culture, visit our Why Work Here blog post.
About the Role
The Data Engineer is responsible for architecting and sustaining the systems that power our organization's data platform. This role involves designing dependable data pipelines, managing data infrastructure, and enabling high-quality datasets that facilitate analytics and informed decision-making throughout the organization.
Data Engineers collaborate closely with analysts, business stakeholders, and fellow engineers to ensure data is accessible, structured, and documented in a manner that promotes consistent and reliable usage. They also take ownership of one or more data domains, being accountable for the pipelines, transformations, and foundational data models that underpin those domains.
Responsibilities
Data Pipeline Development
- Design, construct, and sustain data pipelines that ingest and process data from operational systems into the data warehouse.
- Ensure pipelines are robust, scalable, and maintainable.
- Implement monitoring, logging, and alerting systems to identify failures or anomalies in data processing.
- Troubleshoot and resolve issues related to data pipeline failures or data quality.
Data Modeling and Semantic Layer Support
- Collaborate with analysts and data stakeholders to convert raw datasets into structured, reusable datasets that support reporting and analytics.
- Implement transformations that encapsulate key business logic within the data warehouse.
- Contribute to the development of curated datasets and standardized views that facilitate consistent analysis across various teams and countries.
- Ensure datasets are thoroughly documented and easily understood by downstream users.
Data Quality and Reliability
Establish validation, testing, and monitoring processes to guarantee data accuracy and consistency.
