Data Engineer — AI-Driven Data Pipelines for Starlink

SPACE EXPLORATION TECHNOLOGIES CORP; Hawthorne (CA); On-site; USD 125,000 - 175,000; Full time

Benefits offered by this job

Stock options

Medical, vision, dental coverage

401(k) retirement plan

Paid time off

Job summary

SpaceX is seeking a Data Engineer to join the Starlink Enterprise team in Hawthorne, CA, focusing on improving data quality and building AI-enabled integrations across sales, channel, and enablement workflows. You will partner with Enterprise sales, channel and reseller ops, and enablement to fix messy inputs, reduce manual cleanup, and ship automations that make go‑to‑market workflows more reliable.

The role emphasizes building MCP-backed AI agents and data pipelines to accelerate

Qualifications

• Bachelor’s degree in a STEM discipline.
• 1+ years of professional data or software engineering experience (internship applicable).
• 1+ years of development experience in Python or another modern programming language (SQL, etc.)

Responsibilities

• Improve data hygiene and quality across go-to-market systems.
• Raise the quality of inputs to AI agents and analytics for more accurate outputs.
• Build integrations across internal tools and external systems to reduce manual re-entry.
• Develop Model Context Protocol (MCP) servers and interfaces that connect AI assistants to internal/external systems.
• Design, ship, and iterate AI agents powering Starlink Enterprise workflows.
• Instrument data quality and agent performance with monitoring and feedback loops.

Skills

Python

SQL

Data engineering

Education

Bachelor's degree in Computer Science/Data Science/Physics/Mathematics

Tools

Grok

HubSpot

Clay

Apollo

APIs

Data warehouses

Job description

SpaceX is seeking a Data Engineer to join the Starlink Enterprise team in Hawthorne, CA, focusing on improving data quality and building AI-enabled integrations across sales, channel, and enablement workflows. You will partner with Enterprise sales, channel and reseller ops, and enablement to fix messy inputs, reduce manual cleanup, and ship automations that make go‑to‑market workflows more reliable.

The role emphasizes building MCP-backed AI agents and data pipelines to accelerate