Founding Data Engineer, Pricing and Comps
At a glance
Mid-level Data Engineering role at Clera. Remote, United States · full-time · $160,000–$220,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Build scheduled pipelines that collect sold listings from marketplaces and other outside sources
- Match messy listing descriptions and images to standard items, including across sources with different detail
- Create price estimates that weigh comparable sales by age, condition and how many matches are available
- Track data quality issues such as drift, fraud and stale comparisons before they reach users
- Choose whether to build or buy data sources, licenses and third-party pricing feeds
What you bring
- At least five years building and operating production ETL and data pipelines at scale
- Experience handling messy, adversarial data in marketplaces, pricing, fraud or a similarly noisy area
- Strong SQL skills and hands-on use of modern data tools, such as dbt, Airflow or another listed tool
- Experience with pricing estimates, large-scale record matching and production checks for data quality or anomalies
Who this fits
This founding engineering role suits someone comfortable owning data pipelines and pricing systems while explaining estimate confidence to non-technical stakeholders. The position is hybrid in New York, and visa sponsorship is unavailable.
From the employer
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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