About the Role
Build and own the data systems that turn messy sold-listing information into reliable comparable sales and price estimates. This role is central to the trustworthiness of pricing in a consumer resale marketplace, and you'll partner with computer vision teammates to define how items are matched across sources.
What You'll Do
Build and maintain scheduled, large-scale ingestion pipelines for sold-listing data from multiple sources.
Design entity resolution and deduplication systems that match inconsistent text and images to canonical items.
Develop valuation logic that weighs comparable sales by recency, condition, and sample size.
Create data quality monitoring to identify drift, potential fraud, and stale or unreliable comparisons.
Collaborate with computer vision partners on matching standards across data sources with varying levels of detail.
Evaluate build-versus-buy options for data sources, licensing, and third-party pricing feeds.
What We're Looking For
At least 5 years of data engineering experience, including production ownership of large-scale ETL and data pipelines.
Experience working with messy, adversarial data in a marketplace, pricing, fraud, or similarly noisy domain.
Strong SQL skills and experience with modern data tools such as dbt, Airflow or Dagster, and Spark or similar technologies.
Exposure to statistical estimation or pricing models, including basic regression-based comparable sales logic.
Experience building data quality monitoring and large-scale entity resolution or record-linkage systems.
Sound judgment on data quality tradeoffs, third-party data sources, and licensing decisions, plus the ability to explain pricing confidence and uncertainty to non-technical partners.
Experience in pricing intelligence, real estate valuation, used-vehicle pricing, resale marketplaces, or early-stage startups is a plus.
Compensation & Benefits
Annual salary range: $160,000 to $220,000 USD.
Location
On-site in San Francisco, California, United States.