🕒 3 days ago
Own the end-to-end data platform, designing multi-source ingestion, event-driven processing, and orchestrated workflows that deliver reliable, trusted data for downstream products.
Founding Data Engineer, Pricing and Comps
🕒 2 days ago
Data EngineeringETL PipelinesSQLDbt
📜 Description
- Build and own scheduled ingestion pipelines for sold-listing data from marketplaces and external sources.
- Design entity-resolution systems to match inconsistent listing text and images to canonical items.
- Develop valuation logic that weighs comparable sales by recency, condition, and availability.
- Monitor data quality for drift, fraud, stale comparables, and other integrity issues.
- Make build-versus-buy decisions about data sources, licensing, and pricing feeds.
🛠️ Requirements
- At least 5 years of data engineering experience, including building and owning large-scale production ETL and data pipelines.
- Experience working with messy, adversarial data in marketplace, pricing, fraud, or similarly noisy domains.
- Strong SQL skills and experience with modern data tools such as dbt, Airflow or Dagster, and Spark or similar technologies.
- Experience with statistical estimation or pricing models, including basic regression-based comparable-sales logic.
- Experience designing entity resolution or record-linkage systems at scale, and production monitoring for data quality, drift, or anomalies.
- Experience processing data from multiple external sources, making technical build-versus-buy decisions, and communicating pricing confidence and uncertainty to non-technical stakeholders.
- Pricing intelligence, third-party data licensing, or early-stage startup experience is a plus.
✨ Benefits
- Partner with computer vision colleagues on item matching across sources.
Full job description
About the Role
As the founding data engineer on a marketplace team, you will build the data pipelines and pricing systems that turn inconsistent sold-listing data into reliable comparable sales and estimates. Your work will help ensure users and stakeholders can understand both the price and its confidence.
What You'll Do
Build and own scheduled ingestion pipelines for sold-listing data from multiple marketplaces and external sources.
Design entity resolution systems that match inconsistent listing text and images to canonical items.
Develop valuation logic that weighs comparable sales by recency, condition, and the number of available comps.
Monitor data quality to identify drift, fraud, stale comps, and other integrity issues before they affect users.
Partner with computer vision colleagues to define item matching across sources with differing levels of detail.
Make build-versus-buy decisions about data sources, licensing, and third-party pricing feeds.
What We're Looking For
At least 5 years of data engineering experience, including building and owning large-scale production ETL and data pipelines.
Experience working with messy, adversarial data in marketplace, pricing, fraud, or similarly noisy domains.
Strong SQL skills and experience with modern data tools such as dbt, Airflow or Dagster, and Spark or similar technologies.
Experience with statistical estimation or pricing models, including basic regression-based comparable-sales logic.
Experience designing entity resolution or record-linkage systems at scale, and production monitoring for data quality, drift, or anomalies.
Experience processing data from multiple external sources, making technical build-versus-buy decisions, and communicating pricing confidence and uncertainty to non-technical stakeholders.
Pricing intelligence, third-party data licensing, or early-stage startup experience is a plus.
Compensation & Benefits
Annual base salary: $160,000 to $220,000. Visa sponsorship is not available.
Location
Hybrid, New York, New York, United States.
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