Data Engineer

The Role

We're looking for a data engineer to build robust pipelines that power our pricing model and marketplace insights. Your responsibilities include:

• Design, optimize, and own data pipelines that ingest transaction and listing data from major auction houses and marketplaces.
• Build comprehensive monitoring and alerting systems to track latency, uptime, and coverage metrics.
• Continuously improve data infrastructure by modernizing storage and processing technologies, reducing manual interventions, and optimizing for cost, performance, and reliability.
• Partner with internal teams to understand data usage patterns and ensure pipelines deliver clean, standardized data that meets product requirements.

What you'll do here

Here’s what you’ll be doing:

• Design, optimize, and own data pipelines that scrape, process, and ingest transaction and listing data from major auction houses and marketplaces.
• Build comprehensive monitoring and alerting systems to track latency, uptime, and coverage metrics across all data sources.
• Continuously improve our data infrastructure by modernizing storage and processing technologies, reducing manual interventions, and optimizing for cost, performance, and reliability.
• Partner with internal teams to understand data usage patterns and ensure pipelines deliver clean, standardized data that meets product requirements.

Must-haves

• 3-4 years of experience in data engineering or related fields
• Strong Python proficiency with at least 3 years of hands-on experience
• Proven experience with large-scale data processing using dataframe technologies (Pandas, Polars, PySpark, or similar)
• Hands-on experience with pipeline orchestration tools (Airflow, Dagster, or similar DAG-based systems)
• Solid SQL skills for data analysis and transformation
• Track record of owning at least one data pipeline end-to-end within the past 2 years
• Solid understanding of data quality and the importance of delivering clean and usable data
• A pragmatic mindset focused on delivering value incrementally rather than pursuing perfection

Nice-to-haves

• Experience with web scraping technologies (Selenium, Puppeteer, Beautiful Soup)
• Familiarity with data infrastructure and cloud services (AWS preferred)
• Interest in or knowledge of trading cards, collectibles, or alternative asset markets
• Experience with LLM-based automation tools for data extraction and processing