Homeoffice Data Warehouse Engineer at Zapier
Zapier · San Francisco, United States Of America · Remote
- Professional
About Zapier
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.
Job Posted: September 26, 2025
Location: Americas (North, Central and South America), EMEA (Europe, the Middle East and Africa)
Hi there!
Zapier is hiring a Data Warehouse Engineer to join our Revenue & Finance Data team. In this role, you will be the steward of Zapier’s foundational revenue datasets that support the company's financial health and future growth. You’ll focus on building reusable internal data products to power self-serve analytics, enabling teams across Zapier to gain actionable insights faster.
You’ll help set the technical direction for our analytics ecosystem, designing and evolving core datasets used company-wide and ensuring our data platform scales to support everything from daily operations to advanced AI initiatives.
If you’re interested in advancing your career at a fast-growing, profitable, impact-driven company, then read on…
About You
You are experienced in Data Warehouse Engineering. You bring 4+ years of experience as a Data Warehouse Engineer, Data Engineer, Analytics Engineer, or in a similar role. You excel at self-organizing and managing projects end-to-end, from requirements gathering and solution design to implementation and delivery.
You have a deep understanding of data modeling concepts. You understand the nuances of when traditional data modeling approaches are effective and when they aren’t. You’ve designed data models and ETL pipelines with a focus on ease of use for end consumers, high performance, and scalability.
You strive to align with business goals. You design data models that empower insightful analysis and reporting, always keeping the end goal in mind. You understand the key metrics and their implications, and you work closely with Data Science colleagues and cross-functional stakeholders to ensure your efforts align with broader objectives.
You influence technical standards. You’re familiar with modern data platforms and best practices for scalability and performance. You contribute to shaping your team’s technical direction, including decisions on architecture, tooling, and strategies for technical improvements.
You are proactive and strategic. You proactively develop forward-thinking plans that prioritize stakeholder value and contribute to shaping the team’s technical direction. You stay curious about emerging technologies and stakeholder challenges, striving to connect the two in your work.
You demonstrate AI fluency in your work. You use AI to speed up tasks like scaffolding SQL, brainstorming data models, and drafting documentation, while carefully validating outputs for accuracy and maintainability. You see AI as a collaborative tool that enhances both productivity and solution quality.
Things You’ll Do
Build trusted data products by designing scalable and high-quality pipelines using Airflow, dbt, Databricks, and modeling business-critical metrics like ARR, churn, and NRR, ensuring stakeholders can self-serve confidently.
Shape technical direction by guiding architectural decisions, tooling choices, and strategies to optimize data storage and the analytics landscape.
Enable self-service analytics by partnering with stakeholders across Zapier to understand their analytical needs and creating data products that connect raw data to actionable insights.
Prioritize impact by focusing on high-value projects, transparently pushing back on low-leverage requests, and clearly balancing stakeholder needs with technical feasibility.
Identify opportunities proactively by presenting data-driven solutions before they’re requested and sharing your insights in strategic discussions across Finance, Product, and Revenue.
Elevate the team by mentoring peers, sharing best practices, documenting your work, and making our data ecosystem clearer and more maintainable than before.
