Python is our choice for anything data-heavy: ETL pipelines, scheduled jobs, scraping and enrichment tasks, and backend services where the ecosystem of data and ML libraries genuinely earns its place over a general-purpose framework.
We build these as properly deployed, monitored services — not one-off scripts running on someone’s laptop — with logging and alerting so a failed job gets noticed and fixed instead of silently going stale.
Typical projects: scheduled data pipelines, backend APIs for data-driven products, and automation scripts that would otherwise be a recurring manual task for someone on your team.