Staff Data Engineer, Analytics
Whatnot is the largest live shopping platform in North America and Europe, enabling users to buy, sell, and discover items ranging from trading cards to live plants. As a fast‑growing marketplace recognized as the #1 Best Startup Employer in America by Forbes, the company operates remotely with hubs across the US, UK, Ireland, Poland, Germany, and Australia.
About the role
Data is crucial to Whatnot’s mission to bring people together through commerce. As a Data Engineer you will build and scale the systems that power data‑driven decisions across the company. You will own the analytics data strategy, drive AI‑powered internal tooling, define domain data standards, ensure reporting accuracy, translate raw data into business insight, and set the technical bar for the data organization.
Responsibilities
- Own the analytics data strategy end‑to‑end, defining architecture for internal reporting, business intelligence, agentic tooling, and experimentation, and driving that strategy into production.
- Drive the AI strategy behind internal tools, identifying where agentic and LLM‑powered tooling can add value and leading the roadmap from standards to reliable, scalable infrastructure.
- Define and own the domain data strategy, establishing key metrics, underlying data sources, naming conventions, contracts, and ownership boundaries to maintain a single source of truth.
- Guarantee consistency, accuracy, and speed in reporting by building monitoring, testing, and reconciliation systems that keep dashboards and datasets trustworthy.
- Partner cross‑functionally with analytics, product, engineering, and business stakeholders to turn complex data into clear, actionable insight.
- Set the technical bar for the data organization by establishing best practices for modeling, tooling, and data quality, and mentoring the broader org as an individual contributor leader.
Requirements
- 7+ years of experience as a data or software engineer building data warehouses, distributed data systems, or event‑driven architectures.
- Ability to design and implement data models using dimensional, Data Vault, or ledger‑style techniques for analytical and transactional workloads.
- 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).
- Experience operating cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning.
- Proficiency in production‑grade Python or SQL, and integration with CI/CD and infrastructure‑as‑code workflows.
- Strong collaboration skills, partnering across engineering, product, and analytics to translate messy business requirements into elegant data systems.
- Self‑starter mindset, thriving in a fast‑moving environment and owning both technical design and operational outcomes.
- Must reside within commuting distance of one of the New York, Seattle, Los Angeles, or San Francisco hubs (remote work supported with occasional in‑person time).
Compensation
Base salary range for U.S.‑based full‑time applicants: $207,000 – $290,000 per year, plus benefits and equity. Final salary will be based on level, relevant prior experience, skills, and expertise.
Benefits
- Generous holiday and time‑off policy.
- Health insurance options including medical, dental, and vision.
- Work‑from‑home support and home office setup allowance.
- Monthly allowance for cell phone and internet.
- Care benefits and monthly wellness allowance.
- Annual childcare allowance.
- Lifetime benefit for family planning (adoption or fertility expenses).
- Retirement plans: 401(k) with employer match up to 4 % of base salary (U.S.) and pension plans internationally.
- Monthly allowance to “dog‑food” the app.
- 16 weeks of paid parental leave plus one month gradual return to work (company leave runs concurrently with local statutory leave).