Data Engineer Intern

Skydio•San Mateo, CA

About The Position

Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users, from utility inspectors to first responders, soldiers in battlefield scenarios and beyond. About the role: Join Skydio’s GTM AI team to build the data systems and AI-driven tools that power our go-to-market engine. You will work at the intersection of revenue operations, AI, and data engineering, shipping production-grade solutions that improve data quality, surface insights, and enable intelligent automation. This role focuses on designing structured datasets and internal applications that support AI workflows. You will also contribute to maintaining and optimizing the broader GTM technology stack.

Requirements

Love for data: You enjoy working with complex datasets and take pride in turning messy, inconsistent data into structured and reliable systems.
AI curiosity: You want to understand the full stack of applied AI, from data modeling and semantic retrieval to LLM reasoning and action orchestration.
Builder mindset: You enjoy building solutions from the ground up and iterating quickly.
Business intuition: You understand, or want to learn, how GTM teams operate and what drives revenue outcomes.
Project management skills: You can create project plans that track high-level progress while also managing detailed task execution.
Excellent communicator: You work effectively with sales teams to understand needs, gather requirements, and deliver solutions that support deal execution.

Nice To Haves

Prior Salesforce experience
Experience working with data warehouses (SQL skills highly preferred)
Experience building Business Intelligence dashboards
Experience with prompt engineering and building AI or LLM-powered workflows

Responsibilities

AI data infrastructure: Design and build structured datasets that power LLM workflows and AI agents. Write data transformations, clean messy CRM data, and define reliable schemas across GTM systems.
Data pipelines and automation: Build pipelines to ingest, transform, and validate data from core GTM systems. Improve data integrity and create reusable data models for analytics and AI use cases.
Internal tools and applications: Develop lightweight internal tools using TypeScript and React that allow non-technical teams to interact with structured data, trigger workflows, and access insights.
GTM systems optimization: Support Salesforce and related platforms with data quality improvements, workflow enhancements, and operational reliability initiatives.
Applied AI enablement: Design structured object sets and feature tables that improve LLM performance and reliability. Contribute to building practical AI-driven workflows for GTM teams.