Data Engineer
About The Position
Alt is unlocking the value of alternative assets, starting with the $5B 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 Alt Value is our moat. It is only as good as the data underneath it — and that data lives on dozens of external marketplaces and auction houses that have no interest in making it easy for us to get. That's this job. You own the pipelines that scrape, normalize, and land every transaction and listing that feeds our pricing model. When a comparable sale closes on eBay or at a major auction house, how fast it shows up in Alt Value, and whether it shows up correctly, is your call and your consequence. Pricing decisions, cash advance terms, market analytics, and every dashboard in the company sit downstream of you. The metric you own: Data Coverage. Supporting KPIs are pipeline latency, uptime, and source coverage.
Requirements
- 3-4 years in data engineering or a closely adjacent seat
- Strong Python, 3+ years hands-on, and real large-scale processing with dataframe technologies (Pandas, Polars, PySpark, or similar)
- Orchestration in your hands, not your resume. Airflow, Dagster, or a comparable DAG system — you've built on it, been paged for it, and cleaned up after it
- A pipeline you owned end to end in the past two years. Not a pipeline you contributed to. One that was yours when it broke
- Solid SQL for analysis and transformation
- Startup experience. You understand the pace, and you've worked somewhere the roadmap changed under you
- A pragmatic bias. Value delivered incrementally over the perfect rebuild
Nice To Haves
- web scraping at scale (Selenium, Puppeteer, Beautiful Soup)
- AWS
- LLM-based extraction and processing
- You collect, or you have opinions about the collectibles market.
Responsibilities
- The ingestion layer. Design, optimize, and own the pipelines that scrape, process, and ingest transaction and listing data from major auction houses and marketplaces. Scraper to orchestrator to warehouse, end to end.
- Knowing before we do. Build the monitoring and alerting that tracks latency, uptime, and coverage across every source. A source going quiet should page you, not surprise a pricer three days later.
- Making it cheaper and steadier. Modernize storage and processing, cut manual intervention out of the loop, and optimize for cost, performance, and reliability. Incremental and evidence-based, not a rewrite.
- The consumers. Partner with pricing, ML, product, and analytics to understand how the data actually gets used, and deliver it clean and standardized enough that nobody downstream is writing defensive code around your output.
Benefits
- Medical, dental, and vision coverage (85% covered for employee, up to 50% for dependents)
- HSA/FSA available
- Flexible PTO
- Parental leave at full salary
- $200/month wellness stipend
- $100/month home office stipend
- Free DoorDash membership
- WeWork access
- 401(k)
- Alt Equity to all full-time employees
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
