As the Founding Data Engineer, you will build the data foundation behind reliable pricing for an online marketplace. You will turn inconsistent, noisy sold-listing data into trustworthy comparable items and price estimates, partnering closely with the computer vision lead on matching items across sources.
Build and own scheduled, scalable ingestion pipelines for sold-listing data from multiple marketplaces and external sources.
Design entity resolution logic to match inconsistent listing text and images to canonical items.
Develop valuation logic that accounts for recency, condition, and the number and quality of comparable listings.
Create production data quality monitoring to detect drift, fraud, anomalies, and stale or unreliable listings.
Work with the computer vision lead to define item-matching standards across sources with differing levels of detail.
Make build-versus-buy decisions about data sources, licensing, and third-party pricing feeds.
At least 5 years of data engineering experience, including ownership of large-scale production ETL and data pipelines.
Experience working with messy, adversarial data in marketplaces, pricing, fraud, or a similarly noisy domain.
Strong SQL skills and experience with a modern data stack such as dbt, Airflow or Dagster, and Spark or similar tools.
Experience with statistical estimation or pricing models, including regression-based comparable-item logic.
Experience with entity resolution or record linkage at scale, and production data quality monitoring.
Comfort making ambiguous data quality tradeoffs and communicating pricing confidence and uncertainty to non-technical stakeholders.
Pricing intelligence, data licensing, or early-stage startup experience is a plus.
Annual salary range: $160,000 to $220,000 USD. Visa sponsorship is not available.
Remote, United States and North America.
Build the data engineering foundation for marketplace pricing by creating ingestion pipelines, matching listings to canonical items, and developing reliable valuation systems that improve pricing accuracy and trust.
Build the data engineering foundation for marketplace pricing by owning ingestion pipelines, resolving inconsistent listings into comparable items, and developing reliable valuation systems that improve pricing accuracy and trust.
Own the end-to-end data platform, designing multi-source ingestion, event-driven processing, and orchestrated workflows that deliver reliable, current data for downstream products.
Architect, build, and operate scalable data infrastructure for research and trading, integrating market data, news, and other sources while ensuring data quality, performance, security, and cost efficiency.
Designs and operates reliable data pipelines and models that power customer-facing application features and shared analytics, partnering with engineering and product teams to deliver secure, accurate, accessible data.
