Job Overview
Location
Fully Remote - can be based anywhere in the U.S.
Job Type
Full-time
Category
Software Engineering
Date Posted
April 6, 2026
Full Job Description
📋 Description
- • Data Engineer (Remote-US) at DataKind Inc. – a values-driven, client-facing role focused on building and maintaining data pipelines to improve student graduation rates in partnership with higher education institutions.
- • Day-to-day responsibilities include leading technical onboarding of partner institutions onto the UDTS platform, designing and maintaining scalable data pipelines and APIs, collaborating on-site with institutional data teams to configure dashboards, ensuring data governance and security compliance, and collaborating across engineering, data science, product, and customer success teams.
- • DataKind is a mission-driven nonprofit that leverages data science and AI to advance social impact, with a focus on education, health, climate, and economic opportunity. The role sits within the Data Science team and reports to the Data Science Manager, requiring 20% travel for on-site client support across the U.S.
- • In this role, you will deepen your expertise in data architecture and client engagement, gain experience working with education data systems, strengthen your ability to translate technical concepts for non-technical audiences, and contribute to equitable AI solutions that drive real-world impact in higher education.
Skills & Technologies
About DataKind Inc.
DataKind is a global nonprofit organization that connects data scientists with social change organizations. They leverage the power of data science to solve some of the world's most pressing challenges, working on projects related to poverty, health, education, and the environment. By mobilizing a community of pro bono data scientists, DataKind helps nonprofits and NGOs harness data for greater impact. Their work focuses on building data-driven solutions that can improve decision-making, optimize resource allocation, and ultimately drive positive social change. They aim to make data science accessible and effective for organizations working to make the world a better place.
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