About the Role Build the data foundation for pricing in an early-stage internet marketplace. You will turn noisy sold-listing data into reliable comparable items and price estimates, helping users and investors understand both the value and confidence of each estimate. 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 weights comparable listings by recency, condition, and quantity. • Create production monitoring to detect data drift, fraud, stale comparisons, and integrity issues. • Partner with computer vision teammates to define how items are matched across sources with varying 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 ownership of large-scale production ETL and data pipelines. • Strong SQL skills and experience with a modern data stack such as dbt, Airflow or Dagster, and Spark or similar tools. • Experience working with noisy or adversarial data in marketplaces, pricing, fraud, or a related domain. • Experience with statistical estimation or pricing models, including regression-based comparable sales logic. • Experience building entity resolution or record-matching systems at scale, plus production data quality monitoring. • Ability to make sound data quality tradeoffs and explain pricing confidence and uncertainty to non-technical stakeholders. • Experience processing data from multiple external sources and evaluating data products or integrations is valuable. • Pricing intelligence, data licensing, and early-stage startup experience are helpful. Compensation & Benefits Base salary: $160,000 to $220,000 annually. Visa sponsorship is not available. Location Hybrid, New York, New York, United States. Originally posted on Himalayas