AI coding transforms data engineering: How dltHub's open-source Python library helps developers create data pipelines for AI in minutes

• Berlin-based dltHub raised $8M seed funding for open-source Python data pipeline library
• Tool reached 3M monthly downloads, powers workflows for 5,000+ companies across regulated industries
• Developers now build production data pipelines in minutes using AI coding assistants

Data engineering just got a serious upgrade, and it's not coming from the usual suspects. While enterprise giants like Informatica and Talend have been selling complex GUI-based solutions that require specialized teams, a Berlin startup has quietly built something that lets regular Python developers accomplish the same tasks in minutes instead of months.

The timing couldn't be better. There's a generational clash happening in tech right now between SQL-grounded database veterans and Python-native AI developers who just want to build things quickly. DltHub's library bridges this gap by automating the tedious infrastructure work that traditionally required entire specialized teams. When combined with AI coding assistants, developers are creating custom connectors at a rate of 50,000 per month—a 20x increase since January.

This represents more than just another developer tool—it's a fundamental shift toward what the industry calls the composable data stack. Instead of being locked into monolithic platforms, companies can now build flexible, interoperable infrastructure that adapts as their needs change. For enterprises trying to stay competitive in AI-driven markets, this could mean the difference between hiring expensive specialist teams or empowering existing Python developers to handle data engineering tasks themselves.