Data Engineer

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 performance and scalability across modern data platforms.
• For Product Data Engineering: We're looking for a strong software engineering foundation — designing APIs and data services that power product use cases, applying engineering rigor to build robust, maintainable systems.
• For the Data Platforms team: We're looking for experience with Governance, Privacy, and Security — implementing controls, policies, and infrastructure that uphold compliance and protect data integrity across systems.
• Databricks & Distributed Processing Expertise: You're highly skilled in Databricks, Spark, or similar distributed processing platforms and use them to process large datasets efficiently and cost-effectively.
• Programming and Data Skills: You're proficient in Python and/or Typescript, and strong in SQL. You follow best practices to write clean, efficient, and maintainable code throughout the full software development lifecycle.
• Commitment to Quality and Observability: You care deeply about data reliability and observability. You use testing, monitoring, and alerting to ensure data quality, accuracy, and lineage across pipelines.
• Collaborative and Forward-Looking: You communicate clearly in writing, enjoy sharing knowledge with teammates, and embrace innovation and AI to improve how we build software. You balance pragmatism with action, shipping solutions that simply work and iterating as needed.

Things You'll Do

• Build and Scale Data Services: Design, develop, and maintain scalable backend systems and APIs that directly change the product experiences for our users.
• Collaborate on Data Architecture and Models: Partner with engineering and analytics teams to optimize storage, processing workflows, and database schemas. Define data models and contracts to ensure consistency, accessibility, and scalability across systems.
• Contribute to Standards, Quality, and Governance: Build reliable, observable data systems with strong testing and validation. Champion best practices, golden paths, and CI/CD workflows that uphold data quality, security, and continuous improvement.
• Performance Tuning, Maintenance and Optimization: Continuously monitor and optimize the performance of data workflows, identifying and resolving bottlenecks in data ingestion, transformation, and storage. You will participate in an on-call rotation for data-owned services.
• Develop Reusable Engineering Patterns: Design and implement scalable, reusable engineering patterns and frameworks that enable other engineers to self-serve data capabilities safely and efficiently. You'll empower teams to integrate and utilize data within their systems with minimal dependency on the data engineering team.
• Support Cross-Functional Projects: Work closely with Product, Analytics, and Machine Learning teams to support their data needs, helping them achieve their goals through reliable and insightful data.
• Mentor and Share Knowledge: Act as a resource for junior team members, offering guidance and knowledge-sharing to elevate team expertise and contribute to a culture of learning.

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

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