Software Engineer, Internship - Data Connectors

The Connectivity team builds products that connect our most critical institutions to their most critical data. Our connectors integrate databases, enterprise applications, cloud storage, web services, and streaming systems, enabling customers to bring data into Foundry and write back to their operational systems. From large datasets to real-time events and user-driven interactions, these connections underpin the applications and AI workflows customers build with Foundry and AIP.

You’ll help build Foundry’s first-class connector suite and the shared infrastructure behind it. You’ll work across the stack, taking ownership of connector implementations, developer SDKs, and the systems that build, test, distribute, and run our connectivity software.

Working alongside experienced engineers, you will take on real problems in our production systems. That could mean adding a capability to a Connector, contributing to the infrastructure that runs our assets, or building features to ensure the performance, reliability, and observability of our connectivity suite. You will see your work through design, code review, testing, and release.

• Build and maintain Foundry’s first-class connectors, improving performance and extending support for imports, exports, change data capture, interactive queries, and writeback as external systems and customer needs evolve.
• Improve the infrastructure that builds, tests, packages, and distributes connectors and shared libraries, including tooling across our connector monorepo.
• Design and maintain connectivity SDKs for internal teams and end users, with clear APIs, documentation, testing utilities, and development workflows that make integrations easy to author and maintain.
• Collaborate with product teams to integrate connector execution with job orchestration, streaming, and serverless platforms.
• Debug production issues and performance problems across the stack, turning recurring support problems into durable fixes, automated tests, and better observability.