AI Data Readiness Lead
Core
Own metric registry definitions, make them enforceable in systems, and verify usage by people and AI agents to ensure trustworthy analytics.
Role type
Senior analytics governance engineer (metrics layer)
Builds
Canonical metric definitions, semantic layer implementations, data quality agents, and agent output verification pipelines
Domain
Voice AI / Analytics Engineering / Data Governance
Deliverable
production ML models | dashboards & analysis
Required skills
SQL, semantic layer ownership, resolving conflicting metric definitions, data quality auditing, LLM/AI agent output evaluation, data catalog development
Preferred skills
lakehouse architectures, audit readiness (SOX), usage-based business models, early-stage function building
Technologies
dbt, Cube, LookML, Iceberg, Athena, Trino
Responsibilities
Establish canonical metric definitions and resolve conflicts; Implement definitions in semantic layer and data catalog; Audit reporting estate and retire unused assets; Build data quality checks and agents; Verify AI agent output against ground truth; Enable self-serve access to governed data
Seniority
Senior, hands-on IC