Full Stack Software Engineer

About the Opportunity

DataKind is seeking a Full Stack Software Engineer to build and evolve the UI and API layer of our education data platform. This role owns the software that turns complex educational data into something usable, insightful, and reliable for the institutions we serve. You'll spend most of your time in the web application and API, with regular contributions to the data engineering and infrastructure work that supports it.

Reporting to the VP of Technology, you'll work closely with Data Engineering, Data Science, Product, and Customer Success to ship features that directly affect student outcomes. You'll be a contributing senior technical voice on the team, someone who can take ambiguous product requirements and turn them into shipped, well-architected software.

What You'll Do

Product Engineering (60%)

• Design, build, and maintain web application front end and the APIs that power it.
• Translate product and user requirements, often shaped by direct partner feedback, into clean, maintainable, well-tested code.
• Own features end to end: from technical design through implementation, testing, and deployment.
• Collaborate with Product and Customer Success to understand how institutional users actually work with our education data platform and use that to inform technical decisions.
• Contribute to frontend architecture, component design, and API design standards across the team.

Data Engineering and Infrastructure (25%)

• Contribute to data pipeline and integration work that feeds the education data platform, in partnership with the Data Engineering team.
• Support infrastructure decisions related to application performance, scalability, and reliability.
• Help ensure data flowing into the application layer is validated, well-structured, and secure, including implementation of authentication/authorization (e.g., SSO, OAuth, role-based access control) appropriate for handling sensitive student data.

Collaborate and contribute across DataKind (15%)

• Partner with Data Engineering and Data Science to operationalize models and analytics into production-ready product features.
• Align your work with DataKind’s engineering standards, conduct timely code reviews for your peers, and consistently contribute quality technical documentation.
• Contribute to the continuous improvement and maintenance of internal tooling, engineering process documentation, and workflow automation.

Qualifications

Required

• Deep alignment with DataKind's mission and values, and demonstrated commitment to educational equity and data-driven social impact
• 3-5 years of professional full stack software engineering experience, including meaningful ownership of both frontend and backend systems.
• Advanced proficiency in a modern JavaScript/TypeScript framework (e.g., React) and backend API development.
• Working proficiency in GCP, Python and SQL to support infrastructure and data engineering pipelines.
• Experience designing and building RESTful or GraphQL APIs.
• Experience writing automated tests (unit, integration, and/or end-to-end) and working in a codebase with CI-enforced test coverage.
• Solid understanding of data modeling and how application design intersects with data pipelines.
• Proven ability to collaborate across engineering, data science, and product functions.
• Excellent communication skills, including the ability to explain technical tradeoffs to non-technical stakeholders.

Preferred

• Degree in Computer Science, Software Engineering, or related technical field.
• Experience with PHP, Laravel, OpenAI API, and Anthropic API.
• Experience with Git-based collaborative workflows (e.g., pull requests, code reviews) and CI/CD tooling (e.g., GitHub Actions).
• Experience building or integrating AI-powered features into a product (e.g., LLM integration, recommendation systems, applied ML).
• Experience implementing authentication and authorization patterns (e.g., SSO, OAuth, role-based access control) in a production web application.
• Experience building dashboards or data visualization tools for varied end users.
• Familiarity with education data systems (e.g., SIS, LMS, or student outcome data).
• Experience building systems that comply with SOC2 and/or FERPA.
• Familiarity with civic tech, social impact, or nonprofit data ecosystems.