Alt is unlocking the value of alternative assets, starting with the $5 B trading-card market. We let collectors buy, sell, vault, and finance their cards in one place and we are backed by leaders at Stripe, Coinbase, Seven Seven Six, and pro athletes like Tom Brady and Giannis Antetokounmpo. Our next frontier is real-time pricing at scale—the Alt Value that powers every trade, loan, and product on the platform.
The Role
Are you a data engineer who thrives on building robust pipelines and solving complex data challenges? In this role, you'll own Alt's critical data infrastructure that powers our pricing model and marketplace insights by ingesting transaction and listing data from dozens of external marketplaces. You'll be responsible for ensuring our data pipelines deliver fresh, accurate information that drives pricing decisions, market analytics, and business intelligence across the entire platform.
What you'll do here
- 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.
This is a perfect fit if you...
- Care deeply about data quality and understand that extraction is only the beginning - the real value comes from delivering clean and usable data.
- Thrive in a startup environment where you can make immediate impact and own critical systems end-to-end.
- Take an incremental approach to improvements, preferring evidence-based decisions over wholesale replacements.
- Are intellectually curious about how data flows through systems and passionate about automation opportunities.
- Want to work at the intersection of data engineering and product, understanding how your pipelines directly impact business outcomes.
What you bring to the table
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)
- Track record of owning at least one data pipeline end-to-end within the past 2 years
- Solid SQL skills for data analysis and transformation
- Previous startup exp