GTM Data Operations Engineer

MPLC provides public performance licensing for movies and TV in public and commercial spaces. The GTM Data Operations Engineer owns the US account data pipeline, sourcing, enriching, and qualifying accounts and delivering trusted, sales-ready batches to support sales and demand generation.

Responsibilities:

• Own the US Mid-Market and Enterprise data pipeline: build net-new account detection with Python web      scraping and Clay, qualify accounts against our ideal customer profile, and deliver sales-ready batches every week
• Keep the pipeline sharp and the data trusted: manage enrichment logic, re-score existing accounts, and work closely with sales and demand generation to close the loop when quality falls short
• This is an individual contributor role with real ownership, but not a blank page. You will work to the quality standard and playbooks set by the Principal and Senior, and you are expected to improve them, not just maintain them. You will deliver rep-ready batches on a consistent weekly cadence, and the quality bar is one sales teams have to trust
• We are hiring a GTM Data Operations Engineer to run the data pipeline that sources, enriches and qualifies US accounts, using sources such as ZoomInfo, Dun & Bradstreet, SEC/EDGAR and industry registries. This is an individual contributor role with real ownership of your pipeline

Requirements:

• Clay experience: enrichment tables, waterfall logic and AI agents in production, without burning credits
• Python: you can read, write and debug pipeline and web scraping scripts without a developer
• Quality bias: you know what "sales-ready" means and close the loop before sales has to tell you
• Salesforce fluency: object model, field mapping and CRM hygiene
• AI-first: you have shipped at least one AI workflow in a GTM context and can describe what it produced
• Collaboration: you work well with sales, demand generation, RevOps and IT, and explain data logic in plain language
• 2+ years building GTM data workflows or B2B data pipelines with demonstrable results, such as accounts sourced, acceptance rates improved or manual steps removed
• Familiarity with US B2B data sources (ZoomInfo, Dun & Bradstreet, SEC/EDGAR or similar)