Singer is an open standard for data extraction (taps) and loading (targets). Singer taps are Python scripts that extract data from a source and emit JSON events. When Stitch doesn't have a built-in connector, you build a custom tap. Data engineers and integration specialists build taps for SaaS APIs, internal databases, and custom systems. Salary: $120-180k USD. Time to proficiency: 6-8 weeks. Related to etl-pipelines and api-integration.
Singer is an open standard for data extraction and loading. A Singer tap is a Python script that extracts data from a source (API, database, file) and emits standardized JSON messages (SCHEMA, RECORD, STATE). Building custom Singer taps is how data teams integrate unsupported sources. When Stitch doesn't have a built-in connector, you write a tap and plug it into Stitch. Singer taps are highly reusable: once built, they work with any Singer-compatible target (data warehouse, data lake, analytics platform). The ecosystem is growing; open-source taps are available on GitHub and Singer.io. Demand for custom data integration is high; not all sources have built-in connectors. Building Singer taps is a valuable skill: it's reusable, standardized, and in short supply. Data engineers who can build taps command premium salaries ($150-220k USD senior). It's also a gateway to the modern data stack: understanding Singer opens doors to Meltano, Airbyte (which also supports Singer), and other integration platforms.
| Region | Junior | Mid | Senior |
|---|---|---|---|
| USA | $100k | $150k | $220k |
| UK | $70k | $110k | $160k |
| EU | $75k | $115k | $170k |
| CANADA | $95k | $145k | $210k |
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