Lead ML & Data Engineer (Founding Engineer) — Own Pricing + Market Data at Misprint

Misprint is a peer-to-peer marketplace for graded and sealed Pokémon cards — think StockX, but built for liquidity, transparency, and speed in collectibles. We’re YC-backed, operating in NYC, and growing quickly.

We’re looking for a high-agency ML/Data Engineer to own our market data and pricing systems end-to-end: ingestion, normalization, storage, quality, and the logic/models that turn messy real-world data into reliable pricing and product experiences.

This role sits at the intersection of data + backend engineering. You’ll build and operate the pipelines and services behind pricing and market data, and ship the backend work needed to keep those systems fast, reliable, and scalable in production.

We’re building the data layer that makes Pokémon cards feel tradable like stocks: real-time market signals, smarter pricing, better search/discovery, portfolio analytics, and liquidity tools that help collectors actually execute. If you like turning messy real-world data into features users can feel — this role has a ton of surface area, and is core to our business.

What you’ll do

You’ll work closely with the engineers to:

• Own market data pipelines (scrapers/APIs/ETL) and make them reliable, monitored, and well-documented
• Improve pricing + liquidity logic (cleaning, normalization, deduping, outlier handling, stale-data handling)
• Build systems for data quality + observability (alerts, retries, backfills, audits, freshness metrics)
• Own core datasets/mappings that power product (catalog enrichment, ID mappings, pricing tables)
• Build and maintain backend surfaces that serve data to the product (APIs, queries, internal tooling)
• Partner with product/engineering to ship data-powered features (market stats, trend signals, portfolio analytics, search relevance)

What success looks like (first 60–90 days)

• Data pipelines run reliably with monitoring + alerting and clear recovery paths when things break
• “Critical scripts” are in the repo, reproducible, documented, and not tribal knowledge
• Pricing data is measurably cleaner, fresher, and more trustworthy with clear freshness metrics
• You can confidently ship improvements that increase pricing accuracy and marketplace liquidity

Our stack

• Backend/Data: Postgres (Supabase), Python, some Node
• Infra: Vercel, AWS, Porter, Stripe
• Frontend: React / Next.js / Tailwind (not the focus)

You might be a fit if you…

• Have 3+ years experience in data engineering / ML engineering / backend data systems
• Have owned production pipelines end-to-end: ingestion → transforms → storage → serving
• Are strong at Python + SQL, and comfortable with Postgres in production
• Know how to handle real-world data messiness: duplicates, schema drift, missingness, outliers, backfills
• Can operate independently, communicate clearly, and document systems as you go
• Prefer pragmatic systems that stay reliable over time

Bonus: scraping/automation experience, marketplaces/fintech data, search/relevance, time-series/anomaly detection, or you like Pokémon/collectibles

How to apply

Send:

• Your LinkedIn/GitHub if not in your Work at a Startup Profile (or anything you’re proud of)
• A short note on why you’re interested and what you’ve owned end-to-end
• (Optional) Any experience with Pokémon/TCG/collectibles!

Skills

Python, SQL, PostgreSQL, Data Engineering, ETL, Web Scraping, AWS, Supabase, Monitoring/Alerting