About the role

We're growing the team that keeps our data infrastructure running and our archive growing. This is hands-on work at the intersection of Python, Django, and databases at real scale.

You will:

• Maintain and extend the hundreds of scrapers that continuously pull court data into our system

• Ingest millions of documents and merge them safely into our production database

• Help build and evolve the portal receiving our digitization work at the United States Library of Congress, where a team is scanning millions of pages

• Convert scanned material into structured text and documents, and merge it into the archive without breaking what's already there

• Work on the machine learning processes that identify and remove copyrighted material - a critical safeguard for a nonprofit like ours

• Design batch operations that run across five to ten million records efficiently, without taking the databases down

• Diagnose slow queries, review migrations, and be a person the team can rely on when something in the database needs a second pair of eyes

Hard requirements

Please don't apply if you don't have real experience in these areas:

• Python, professionally and at depth

• Django - this is the framework we build on and the single most important skill for this role

• Strong database experience. We run Postgres, but we care more about your fundamentals than the specific engine: you should be comfortable reading an execution plan, tracking down why a query is slow, reasoning about indexes, and handling migrations that don't go as planned

• Web scraping - building, maintaining, and debugging scrapers in production

Nice to have

• Celery, Redis, Kubernetes

• Machine learning applied to document processing (OCR, classification, extraction)

• Experience with legal data, civic tech, govtech, or open data

• Elasticsearch or similar search infrastructure

• A genuine interest in law, access to justice, or social justice work — it's what we do every day