opengreenhousea16z
Senior Analytics Engineer
Zipline
LocationSouth San Francisco, California, USA, Aviary - SSF
Last observed2026-06-23 23:25:44.662340
Job ida16z-zipline:greenhouse:5034594003
About Zipline Zipline is the world’s largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. We design, build, and operate the world’s largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products. Our customers include the world’s largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we’ve built to enable seamless, reliable, global operations. Our system strengthens supply chains, reduces congestion, and gives people time back. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe. We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people’s lives and by scaling the future of logistics. We are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record breaking speeds. About You and The Role Zipline’s Application Software team builds the systems that power every part of our business, from the factory floor to real-time delivery operations. We are responsible for the “operating system” of Zipline: critical applications that manage hardware production and inventory, fuel demand generation and customer engagement, enable data-driven decision making, and orchestrate fulfillment, flight, and delivery at scale. Our work spans internal platforms that streamline manufacturing, supply chain, and financial workflows, as well as external-facing applications that allow customers to place and track orders. By connecting every corner of the business through software, we ensure Zipline can operate efficiently, intelligently, and globally. As a Senior Analytics Engineer on our team, you’ll play a key role in unlocking the full potential of data from these systems. You will build and optimize data pipelines, transform raw information to make connections and develop analysis-ready datasets, and serve as a trusted expert for the company’s most important and complex data questions. As a result, Zipline leaders will have high-quality and actionable data to make more informed decisions, innovate faster, and serve our customers better. What You'll Do Bridge the gap between business problems and the data required to address them. Become a trusted partner for customer and operational teams, identifying and anticipating analytical needs and delivering high-impact solutions and insights. Develop and maintain scalable data pipelines to ensure stable, accurate, and reliable data flows seamlessly across systems. Build semantic views, governed metrics, and reusable data models that make our data easier to understand, trust, and use across both traditional BI tools and AI-powered workflows. Design, develop, and optimize models to consolidate raw data from multiple platforms and transform it into clean, reusable datasets. Help improve and extend our internal AI analytics harness, making it increasingly effective at answering data questions accurately, transparently, and in ways that drive real operational impact. Use AI tools thoughtfully to accelerate your own work, from analysis and documentation to modeling and exploration, while applying strong judgment about where human review, validation, and business context are required. Partner with engineers to improve data
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