Data Engineer

Role

Data is crucial to Whatnot’s mission to bring people together through commerce.

As a 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, sales, marketing, 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—then implement it in production. You’ll make architectural decisions around storage formats, compute patterns, and SLAs that balance cost, scalability, and consistency.
• Build mission-critical pipelines. Develop and operate streaming and batch data workflows that process high-volume events across multiple domains—user activity, transactions, experimentation, marketing performance, and operational telemetry—with tight guarantees for latency, completeness, and accuracy.
• Design and implement canonical models. Create domain-oriented data models that serve as the source of truth for analytics, ML, and real-time applications. Establish and enforce modeling standards, ownership boundaries, and data contracts across teams.
• Enforce data quality at scale. Build 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.
• 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.

You

• Have 3+ 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, BigQuery, 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, analytics—to translate messy business requirements into elegant data systems.
• Thrive as a self-starter in a fast-moving environment, owning both the technical design and the operational outcomes of your work.

Compensation

For Full-Time (Salary) US based applicants: $180,000/year to $260,000/year + benefits + equity.

Benefits

• Generous Holiday and Time off Policy
• Health Insurance options including Medical, Dental, Vision
• Work From Home Support
  • Home office setup allowance
  • Monthly allowance for cell phone and internet
• Care benefits
  • Monthly allowance for wellness
  • Annual allowance towards Childcare
  • Lifetime benefit for family planning, such as adoption or fertility expenses
• Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary)
• Monthly allowance to dogfood the app
• Parental Leave: 16 weeks of paid parental leave + one month gradual return to work