Data Engineer, CX

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.

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 work directly with stakeholders across the business – such as product, customer experience, logistics, finance, and trust teams – to design reliable data architectures, ship resilient pipelines, and create the foundational data products that power Whatnot's internal and external growth.

On any given day, you will:

• Own data architecture end-to-end. Define how we capture, model, and serve critical business data. You'll make architectural decisions around storage formats, compute patterns, and SLAs that balance cost, scalability, and consistency.
• Lead the CX and Logistics Data Domains. Act as the data owner for our Customer Experience (CX) and Logistics domains, including ownership of data foundations and stewardship for several mission-critical metrics and concepts (refunds, customer satisfaction and sentiment, shipping, margin, and more).
• Design and implement canonical models. Create domain-oriented data models that serve as the source of truth for analytics, ML, LLMs, and real-time applications. Establish and enforce modeling standards, ownership boundaries, and data contracts across teams.
• Enforce data quality ld tests, lineage, monitoring, and reconciliation systems that make every dataset observable and every anomaly actionable.
• Automate operational workflows. Partner with business systems and platform teams to eliminate manual data handoffs and reconcile data across services, warehouses, and external systems. Experience ingesting and operationalizing third party-created data is a plus.
• Enable insights and experimentation. Support analytics, ML, and product engineering teams by exposing high-quality, low-latency data through semantic layers, APIs, and real-time query systems. Stand up platforms to enable novel experimentation approaches within the company.

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 5+ 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, Great Expectations).
• Have operated cloud data warehouses such as Snowflake, Big Query, or Redshift, including schema design, cost optimization, and workload tuning.
• Are comfortable writing production-grade code in Python or SQL languages, and integrating with CI/CD and infrastructure-as-code workflows.
• Enjoy partnering across disciplines – engineering, product, operations, analytics – to translate messy business requirements…