Data Engineer

Data Engineer at Zapier

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Zapier is hiring for two Data Engineer openings with distinct location requirements:

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

Two Data Engineer Roles, Two Teams

Are you passionate about leveraging data to transform software products? Zapier is hiring two Data Engineers to join its Data organization: one on the Product Data Engineering team and one on the Data Platforms team. In these roles, you will 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.

The Product Data Engineering team focuses on building and scaling data systems that power key parts of Zapier's product, from personalization and information retrieval for AI systems to usage analytics and billing. This team partners closely with product and engineering teams to make data more reliable, discoverable, and actionable, improving how users experience Zapier.

The Data Platforms team builds and maintains the foundational data infrastructure that enables reliable, secure, and scalable data operations across Zapier. This team focuses on governance, privacy, and security, ensuring data integrity, compliance, and trust across the company.

About You: Ideal Data Engineer Candidate

• 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 seek a strong software engineering foundation, including designing APIs and data services that power product use cases, applying engineering rigor to build robust, maintainable systems.
• For the Data Platforms team: We seek experience with Governance, Privacy, and Security, including implementing controls, policies, and infrastructure that uphold compliance and protect data integrity across systems.
• Databricks & Distributed Processing Expertise: You are highly skilled in Databricks, Spark, or similar distributed processing platforms, using them to process large datasets efficiently and cost-effectively.
• Programming and Data Skills: You are 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.

What You'll Do as a Data Engineer

• 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 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 will 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.

How to Apply at Zapier

At Zapier, we believe that diverse perspectives and experiences make us better, which is why we have a non-standard application process designed to promote inclusion and equity. We encourage you to apply even if your skills and experiences don’t exactly match the job description. All we ask is that you answer a few in-depth questions in our application that would typically be asked at the start of an interview process. This helps speed things up by letting us get to know you and your skillset a bit better right out of the gate. Please be sure to answer each question; the resume and CV fields are optional.

Education is not a requirement for our roles. Zapier is an equal-opportunity employer, committed to diversity, inclusion, belonging, and equity. We consider all qualified applicants, including those with criminal histories, consistent with applicable laws.

Zapier is committed to inclusion and will provide reasonable accommodations for individuals with disabilities. If accommodations are needed, please contact jobs@zapier.com.

The anticipated application window is 30 days from the date job is posted, unless circumstances require it to close sooner or later, or if the position is filled.

Key Skills/Competency

• Data Pipelines
• Cloud Platforms (AWS/GCP/Azure)
• Databricks & Spark
• Python / Typescript
• SQL
• Data Modeling
• API Design
• Data Governance
• Data Observability
• CI/CD