Data Engineer

Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. We’re re-defining e-commerce by blending community, shopping, and entertainment into a community just for you. As a remote co-located team, we’re inspired by innovation and anchored in our values. With hubs in the US, UK, Germany, Ireland, and Poland, we’re building the future of online marketplaces –together.

From fashion, beauty, and electronics to collectibles like trading cards, comic books, and even live plants, our live auctions have something for everyone.

And we’re just getting started! As one of the fastest growing marketplaces, we’re looking for bold, forward-thinking problem solvers across all functional areas. 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, 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

We’ve learned that low ego, a growth mindset, and a bias toward action create outsized impact at Whatnot. You’ll thrive here if 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.

If designing the data backbone that powers Whatnot’s growth, insights, and product innovation excites you, we’d love to meet you.
Team members in this role are required to be within commuting distance of our New York City, Los Angeles, Seattle, and San Francisco hubs.
💰Compensation

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

The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity.

• 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) and Pension plans internationally

• Monthly allowance to dogfood the app

  • All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!).

• Parental Leave

  • 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.

Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.