AI at Zapier

At Zapier, we build and use automation every day to make work more efficient, creative, and human. So if you’re using AI tools while applying here - that’s great! We just ask that you use them responsibly and transparently.

Check out our guidance on How to Collaborate with AI During Zapier’s Hiring Process, including how to use AI tools like ChatGPT, Claude, Gemini, or others during our hiring process - and when not to.

Job Posted: October 20, 2025

Updated: November 26, 2025

Location: We’re hiring for two Data Engineering openings, each with different location requirements:

Product Data Engineering: Americas only.
Data Platforms: Americas or EMEA.

Hi there!

Are you passionate about leveraging data to transform software products? We’re hiring two Data Engineers to join Zapier’s Data organization: one on Product Data Engineering and one on Data Platforms team. In these roles, you’ll help shape the future of how data powers Zapier’s products and platform, working with a modern stack to build robust APIs, services, and foundations that other teams build on.

Two roles, two teams

Product Data Engineering focuses on building and scaling the data systems that power key parts of Zapier’s product — from personalization and information retrieval for AI systems to usage analytics and billing. The team partners closely with product and engineering teams to make data more reliable, discoverable, and actionable, helping improve how users experience Zapier.
Data Platforms builds and maintains the foundational data infrastructure that enables reliable, secure, and scalable data operations across Zapier. The team focuses on governance, privacy, and security — ensuring data integrity, compliance, and trust across the company.

Our philosophy for hiring

Our Commitment to Applicants
Culture and Values at Zapier
Zapier Guide to Remote Work
Zapier Code of Conduct
Diversity and Inclusivity at Zapier

About You

Experienced Data Engineer: You have 4+ years of experience building and maintaining scalable, reliable data pipelines and infrastructure in cloud environments (AWS, GCP, or Azure). You apply best practices for per