Data Engineer and Analyst - DevTech Systems

DevTech is a mission-driven firm specializing in innovative, data-driven solutions that help governments, civil society, and the private sector strengthen public financial systems, unlock investment, and make informed decisions in complex environments. We combine advanced analytics, contextual insight, and blended finance strategies to deliver practical, forward-looking solutions worldwide. Guided by our core values of integrity, innovation, evidence-driven impact, resilience, and collaboration, DevTech works transparently and in close partnership with clients and communities to achieve measurable results and lasting impact.

DevTech is looking for a Data Engineer and Analyst to work as an institutional contractor on its Analytics, Data, Visualization, and Information Services 2.0 (ADVISE 2.0) contract with the United States Department of State. The Data Engineer and Analyst will work with the Office of Global Food Security (GFS) to support Humanitarian Assistance (HA) across the State Department. The Data Engineer and Analyst will support the Humanitarian Data, Assessment, & Coordination unit within GFS’ Technical Quality & Assurance Division. The Humanitarian Data, Assessment, & Coordination unit strives to create and share decision support products with humanitarian assistance decision makers to improve their understanding of humanitarian needs, internal and external humanitarian data, and to improve the quality and targeting of global humanitarian assistance in crisis settings.

Overall, we are seeking a data-savvy professional who can bridge engineering and analysis. This hybrid Data Engineer and Data Analyst role involves building and maintaining data systems, exploring and interpreting complex humanitarian datasets, and empowering colleagues to make informed, evidence-based decisions. The ideal candidate combines technical expertise with intellectual curiosity, strong analytical skills, and a passion for using data to support humanitarian outcomes.

Responsibilities are as follows:

Data Engineering & Infrastructure (≈60%)

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows to support humanitarian operational and analytical needs. • Build and optimize data models, schemas, and cloud-based data architectures to support dashboards, machine learning workflows, and advanced analytics. • Respond quickly to database problems that arise and carry out periodic maintenance and troubleshooting. Monitor the system performance by performing regular tests, troubleshooting, and integrating new features. • Integrate heterogeneous humanitarian data sources. • Implement data quality, validation, and monitoring processes to ensure accuracy, reliability, and transparency. • Maintain an awareness of trends and developments in database maintenance. • Maintain documentation, metadata, and data governance standards in alignment with state department po