Improve data hygiene and quality across go-to-market systems — identify bad, missing, duplicate, and stale records; implement validation, enrichment, and remediation so higher-quality data enters our system of record, opportunity, partner/reseller, and enablement workflows

Raise the quality of inputs to AI agents and analytics so outputs (recommendations, deal status, enablement answers, reporting) are more accurate, trustworthy, and actionable

Build integrations across internal tools and external systems so deal, customer, and partner context flows cleanly between sales, channel ops, and operational platforms — reducing manual re-entry and preventing quality issues at the source

Develop Model Context Protocol (MCP) servers and related interfaces that connect AI assistants (including Grok) to internal and external go-to-market systems, with an emphasis on reliable, well-scoped access to the right data and tools

Design, ship, and iterate AI agents that power Starlink Enterprise go-to-market workflows

Contribute to AI-powered applications and automations that accelerate lead-to-revenue cycles, working within the additional datasets and systems architecture owned by the team

Instrument data quality and agent performance with monitoring and feedback loops — catching regressions early and tying improvements to outcomes (e.g., cleaner pipeline, faster cycle times, higher adoption and trust)

Partner closely with sales, sales ops, channel/reseller ops, and enablement to turn recurring data-quality problems and manual processes into durable automations and standards

Create reusable tools, checks, and documentation that help the team maintain data quality and extend agents over time

Data Engineer (Starlink)

Responsibilities

Qualification

Required

Preferred

Benefits

Company

SpaceX

More roles at SpaceX