Note: The job is a remote job and is open to candidates in USA. Alt is unlocking the value of alternative assets through a platform for buying, selling, vaulting, and financing trading cards. The Data Engineer will own end-to-end ingestion pipelines that scrape, normalize, monitor, and load transaction and listing data from external marketplaces and auction houses to power real-time pricing, analytics, and downstream products.
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
- Build for reuse first. Most of the ingestion stack — auth handling, retries, session and proxy management, monitoring — should generalize across sources. Go deep and custom only where a specific source's structure actually requires it
- 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
- The consumers. Partner with pricing, ML, product, and analytics to deliver data clean and standardized enough that nobody downstream is writing defensive code around your output
Skills
- 3-4 years in data engineering or a closely adjacent seat
- Modern web scraping at scale — Playwright or comparable, plus the ability to impersonate a real browser at the network layer (TLS/request fingerprinting) when a plain HTTP client gets flagged. Selenium alone doesn't cut it anymore
- Strong Python, 3+ years hands-on. Solid SQL for analysis and transformation
- 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
- Judgment on when to generalize and when to go bespoke — you don't rebuild the same infrastructure per source, and you don't force a one-size-fits-all approach onto a source that needs custom handling
- 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
- Cloud development experience (AWS, GCP)
- LLM-based extraction and processing at scale (e.g. LLM-as-a-Judge, Agent loops), not just UI-based Q&A and simple Skill building
- 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
- Bonus: large-scale dataframe processing (Pandas, Polars, PySpark)
- You collect, or you have opinions about the collectibles market
Benefits
- Equity for all full-time employees
- For full-time Employees: We cover 85% of your medical, dental, and vision, and up to 50% for dependents. HSA/FSA available
- Generous PTO that people actually take
- Parental leave at full salary
- $200/month wellness + $100/month home office stipend
- Free DoorDash Pass membership
- Remote-first (for most positions), with WeWork access when you want a room with other humans
- 401(k)
- Alt Equity to all full-time employees
Company Overview