Gtm Data Engineer Intern

Skydio · Defense · San Mateo, CA +1 · Operations

The GTM Data Engineer Intern will build data systems and AI-driven tools for the go-to-market engine, working at the intersection of revenue operations, AI, and data engineering. Responsibilities include designing structured datasets for LLM workflows and AI agents, building data pipelines, developing internal tools with TypeScript and React, optimizing GTM systems like Salesforce, and enabling applied AI. The role requires a love for data, curiosity about applied AI, a builder mindset, business intuition, project management skills, and strong communication.

What you'd actually do

  1. Design and build structured datasets that power LLM workflows and AI agents.
  2. Build pipelines to ingest, transform, and validate data from core GTM systems.
  3. Develop lightweight internal tools using TypeScript and React that allow non-technical teams to interact with structured data, trigger workflows, and access insights.
  4. Support Salesforce and related platforms with data quality improvements, workflow enhancements, and operational reliability initiatives.
  5. Design structured object sets and feature tables that improve LLM performance and reliability.

Skills

Required

  • design structured datasets
  • power LLM workflows
  • AI agents
  • data transformations
  • clean messy CRM data
  • define reliable schemas
  • build pipelines
  • ingest, transform, and validate data
  • improve data integrity
  • create reusable data models
  • analytics and AI use cases
  • develop internal tools
  • TypeScript
  • React
  • structured data
  • trigger workflows
  • access insights
  • support Salesforce
  • data quality improvements
  • workflow enhancements
  • operational reliability
  • design structured object sets
  • feature tables
  • improve LLM performance and reliability
  • build practical AI-driven workflows
  • GTM teams
  • working with complex datasets
  • turning messy, inconsistent data into structured and reliable systems
  • understand the full stack of applied AI
  • data modeling
  • semantic retrieval
  • LLM reasoning
  • action orchestration
  • building solutions from the ground up
  • iterating quickly
  • understand how GTM teams operate
  • what drives revenue outcomes
  • create project plans
  • track high-level progress
  • manage detailed task execution
  • work effectively with sales teams
  • understand needs
  • gather requirements
  • deliver solutions
  • support deal execution

Nice to have

  • Salesforce experience
  • data warehouses
  • SQL
  • Business Intelligence dashboards
  • prompt engineering
  • building AI or LLM-powered workflows

What the JD emphasized

  • power LLM workflows
  • AI agents
  • LLM workflows
  • AI agents
  • data pipelines
  • ingest, transform, and validate data
  • data integrity
  • reusable data models
  • analytics and AI use cases
  • internal tools and applications
  • structured data
  • trigger workflows
  • access insights
  • GTM systems optimization
  • Salesforce
  • data quality improvements
  • workflow enhancements
  • operational reliability
  • Applied AI enablement
  • structured object sets
  • feature tables
  • improve LLM performance and reliability
  • practical AI-driven workflows
  • GTM teams
  • complex datasets
  • messy, inconsistent data
  • structured and reliable systems
  • full stack of applied AI
  • data modeling
  • semantic retrieval
  • LLM reasoning
  • action orchestration
  • building solutions from the ground up
  • iterating quickly
  • GTM teams operate
  • revenue outcomes
  • project management skills
  • create project plans
  • track high-level progress
  • detailed task execution
  • Excellent communicator
  • sales teams
  • understand needs
  • gather requirements
  • deliver solutions
  • support deal execution
  • prompt engineering
  • building AI or LLM-powered workflows

Other signals

  • designing structured datasets
  • power LLM workflows
  • AI agents
  • data transformations
  • clean messy CRM data
  • reliable schemas
  • data pipelines
  • ingest, transform, and validate data
  • data integrity
  • reusable data models
  • analytics and AI use cases
  • internal tools and applications
  • TypeScript and React
  • structured data
  • trigger workflows
  • access insights
  • GTM systems optimization
  • Salesforce
  • data quality improvements
  • workflow enhancements
  • operational reliability
  • Applied AI enablement
  • structured object sets
  • feature tables
  • improve LLM performance and reliability
  • practical AI-driven workflows
  • GTM teams
  • complex datasets
  • messy, inconsistent data
  • structured and reliable systems
  • full stack of applied AI
  • data modeling
  • semantic retrieval
  • LLM reasoning
  • action orchestration
  • building solutions from the ground up
  • iterating quickly
  • GTM teams operate
  • revenue outcomes
  • project management skills
  • create project plans
  • track high-level progress
  • detailed task execution
  • Excellent communicator
  • sales teams
  • understand needs
  • gather requirements
  • deliver solutions
  • support deal execution
  • prompt engineering
  • building AI or LLM-powered workflows