A company's marketing site tells you what it wants you to believe. Its job postings tell you what is actually true. Nobody writes "experience with Kafka, Snowflake, and dbt required" into a job ad as branding; they write it because a hiring manager needs someone who can operate the stack they really run.
That makes job postings one of the best technographic and intent data sources available, and it is almost entirely ignored by the standard GTM stack. This post covers what you can extract from hiring data, where the extraction goes wrong, and how to build a pipeline for it.
What a job post leaks
The current stack. Requirements sections enumerate the production stack more honestly than any tech-detection crawler. Website-based technographics tools (BuiltWith, Wappalyzer, and their alternatives) see what ships to the browser: the analytics snippet, the framework, the CDN. They cannot see Datadog, Terraform, Snowflake, Airflow, or anything else that lives behind the firewall. Job posts name those tools constantly.
The next stack. "Nice to have" sections and phrases like "help us migrate to" leak roadmaps. A company posting three roles mentioning Kubernetes when its current infra jobs say ECS is telling you about a migration before any analyst report does.
