Engineering Manager, Data Engineering

We're humans who simply think computers should do more work.

At Zapier, we’re not just making software—we’re building a platform to help millions of businesses globally scale with automation and AI. Our mission is to make automation work for everyone by delivering products that delight our customers. You’ll collaborate with brilliant people, use the latest tools, and leverage the flexibility of remote work. Your work will directly fuel our customers’ success, and as they grow, so will you.

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.

Are you excited about building systems that make data accessible, reliable, and impactful across a fast-growing product ecosystem? We’re looking for a Manager, Data Engineering to lead a team that designs and scales the data services and frameworks powering product experiences and AI capabilities at Zapier.

As the Manager of Data Engineering, you’ll guide a team of talented engineers in developing APIs, backend systems, and reusable engineering patterns that help the rest of Zapier build with data safely and efficiently. You’ll shape how we serve data, scale our infrastructure, and collaborate across Product, Machine Learning, and Analytics to unlock new possibilities.

• Our Commitment to Applicants

• Culture and Values at Zapier

• Zapier Guide to Remote Work

• Zapier Code of Conduct

• Diversity and Inclusivity at Zapier

• You have 8+ years of experience in data and/or software engineering, including 3+ years in a people management role. You’ve built and scaled data or backend systems in cloud environments and guided teams through the evolution from pipelines to services.

• You possess strong leadership and strategic planning skills. You’ve successfully managed technical teams, set clear goals, and driven your team to meet them. You have a knack for aligning data capabilities with business objectives and can effectively communicate the value of these capabilities to both technical and non-technical stakeholders.

• You have a strong software engineering background. You understand how to design and operate APIs, distributed systems, and data-serving layers that handle growth, reliability, and cost efficiency. You think in systems and build for reuse.

• You are skilled in stakeholder management. You excel at building relationships across the organization, working closely with Product, Engineering, and other teams to ensure alignment and drive collaborative success. You’re adept at translating complex technical concepts into clear, actionable insights for a variety of audiences.

• You are fluent in AI and its implications. You use AI to enhance your team’s productivity and creativity, but you also understand how it reshapes opportunity space — influencing business priorities, technical strategy, and the way data products are built and consumed.

• You prioritize quality, observability, and reliability. You help your team design systems that are tested, monitored, and observable, ensuring data integrity and confidence in production.

• You understand that perfect is the enemy of good. You will default to action by initially shipping solutions that simply work and work simply while iterating as needed.

• You excel at leading and developing people. You create clarity and alignment, provide coaching and feedback, and help engineers grow in both technical and personal dimensions. You balance autonomy with accountability and celebrate impact over output.

• Lead and develop the Data Engineering team: Manage, coach, and grow a distributed team of engineers focused on building scalable, reusable data systems and APIs.

• Shape our data services and platform strategy: Define the architectural vision for how data is ingested, processed, served, and accessed across Zapier. Drive toward simplicity, scalability, and self-service.

• Develop reusable engineering patterns: Champion the creation of frameworks and abstractions that enable engineers across Zapier to safely self-serve data capabilities without depending on the data team for every integration.

• Build reliable and observable systems: Ensure data pipelines, APIs, and services meet high standards for quality, performance, and uptime. Establish operational metrics and incident practices for data-owned systems.

• Champion governance, CI/CD, and operational excellence: Ensure data systems and practices uphold security, privacy, and compliance standards while driving automation, reliability, and continuous improvement across the data platform.

• Collaborate across teams: Work with Product and AI/Machine Learning teams to align data solutions with their goals — from powering personalization and AI experiences to making our backend systems more robust and resilient.

• Encourage AI-assisted development and innovation: Drive adoption of AI tools and practices within the team, improving productivity and experimentation while fostering critical thinking about responsible use.

• Plan and deliver business impact: Partner with peers and leadership to prioritize initiatives, define success metrics, and deliver projects that advance Zapier’s mission and data maturity.

• Foster a culture of learning and excellence: Run demos, retros, and design reviews that reinforce curiosity, quality, and collaboration across the broader data organization.

Our stack is best summed up by: Databricks, AWS, Python/Typescript, Kafka, dbt and Airflow.