AnywhereHired, a remote job board for visa sponsorship and junior-friendly roles

Built a remote job board. Then realized the scraper wasn’t the real product.

After launching AnywhereHired, I started building the data layer behind it:

daily job snapshots
pipeline run tracking
data quality reports
trend analytics over time
a DuckDB warehouse
Plotly dashboards for internal monitoring
What I’ve learned so far:

scraping jobs is only step one
data quality, freshness, and trust in the metrics matter much more than I expected
filters like junior-friendly and visa sponsorship are far more valuable than generic “remote jobs” browsing
even small products benefit from basic observability and analytics infrastructure
The stack is still simple: Flask, Scrapy, SQLite, DuckDB, Plotly, cron

It’s been fun watching this go from “job board side project” into something that feels more like a small data platform.

If you’ve built a scraper-heavy product, I’d love to know: what mattered more for you long-term — better acquisition, better data quality, or better UX?