Staff Data Engineer, Analytics

🚀 Join the Future of Commerce with Whatnot! Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops. As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact. We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce. 💻 Role Data is crucial to Whatnot’s mission to bring people together through commerce. As our newest Data Engineer , you’ll build and scale the systems that power data-driven decisions across the company. You’ll own the strategy that empowers the Analytics team’s tooling which includes but is not limited to internal reporting, agentic tooling, and experimentation. On any given day, you will: Own the analytics data strategy end-to-end. Define how internal reporting, business intelligence, agentic tooling, and experimentation infrastructure are architected, then drive that strategy into production. You'll make the calls on data models, tooling investments, and delivery patterns that balance speed, accuracy, and long-term scalability. Drive the AI strategy behind our internal tools. Identify where agentic and LLM-powered tooling can supercharge how the business understands itself, then lead the roadmap that turns those bets into reliable, adopted systems — from prompt and data standards to the infrastructure that makes them trustworthy at scale. Define and own the domain data strategy. Establish the metrics that matter, the underlying data that powers them, and the standards for how they're modeled, named, and used across the org. Set the contracts and ownership boundaries that keep every team building on the same source of truth. Guarantee consistency, accuracy, and speed in reporting and intelligence. Build the monitoring, testing, and reconciliation systems that make every dashboard and dataset trustworthy — so decision-makers never have to wonder if the number in front of them is right or current. Translate raw data into business understanding. Partner cross-functionally with analytics, product, engineering, and business stakeholders to turn complex data into clear, actionable insight — shaping not just what data exists, but how the business actually uses it to make decisions. Set the technical bar for the data organization. Establish best practices for modeling, tooling, and data quality that other engineers and analysts build on, and mentor the broader org toward higher craft as an IC lead — without a management chain, but with organization-wide influence. 👋 You People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it. Have a minimum of 7+ years of experience as a data or software engineer building data warehouses, distributed data systems, or event-driven architectures. Can design and implement data models using dimensional, Data Vault, or ledger-style techniques that support analytical and transactional workloads. Have deep hands-on expertise with modern data tooling across ingestion (e.g., Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), and observability (Monte Carlo,