Data pipelines
Coordinates the data ingestion, transformation, and quality work that analytics and ML products depend on.
Also called: ETL, data engineering, data platform, streaming data, data quality
How the score was computed
- News signal0.05
News signal 0.05: 1 verified article(s) mention this skill, weighted by how recent they are, source type, and evidence level (0.14 of 3 needed for a full signal). Strong means at least 0.4.
- JD signal31%
JD signal 0.31: 4 of 16 job descriptions require it and 2 prefer it (preferred counts 0.5). Strong means at least 35%.
- Momentum-1.00
Momentum -1.00: 0 article(s) in the last 30 days vs 1 in the 180 days before, compared per day.
In the news 1
- Making Your Data Ready for Agentic AI
martinfowler.com · Blog · Aug 27, 2026
“Autonomous agents supply none of that.”
Moderate evidenceAI-generated · Shift ExtractionData teams are told to build data for autonomous agents instead of human analysts, so data must carry trust, meaning, and quality checks that people used to supply themselves.
In job postings 6
- Nurorequired
Lead Technical Program Manager, AI Platform · Lead (people manager) · captured Oct 27, 2026
“data flywheel for developing AI systems”
- Figmapreferred
Technical Program Manager - AI Tooling · Mid (5+ yrs) · captured Oct 27, 2026
“identity platforms, data platforms, vendor evaluation, or procurement processes”
- Coinbaserequired
Technical Program Manager, CX Intelligence & AI · Senior (10+ yrs) · captured Oct 27, 2026
“Fluency with AI/ML systems, automation platforms, data pipelines, and CX technologies”
- Databricksrequired
Staff Technical Program Manager- Security · Staff · captured Oct 27, 2026
“anomaly detection pipelines”
- Redditrequired
Staff Technical Program Manager, Infrastructure · Staff (IC5) · captured Oct 27, 2026
“data platform architectures”
- Waymopreferred
Technical Program Manager - Onboard Systems, ML Modeling · Mid (5+ yrs) · captured Oct 27, 2026
“data labeling, data generation and packaging for model training”
Waiting for an editor (not counted yet)
- Making Your Data Ready for Agentic AI: The article calls for data contracts and quality validation so data is accurate, fresh, and checked before an agent ever sees it.
- Extractor confidence 0.60 is below 0.7
- Proposed new skill "Data contracts and quality engineering": Defines and enforces data contracts and validation rules so data is accurate, fresh, and trusted before AI agents consume it.