Role Overview: We’re building an AI-ready data platform on top of our BigQuery warehouse and looking for a Senior Data Engineer to lead how AI interacts with data. This is a data engineering role with real AI exposure — focused on structure, semantics, and control, not model training. You will define how data is understood, accessed, and used by AI systems across the company. How We Build: We use AI-native workflows (Claude Code). A core part of the system is structured instruction layers (skill.md) that define: * how AI queries data * how metrics are interpreted * what is allowed vs restricted You will design both: * the data layer * and the instruction layer that makes it usable by AI Scope: ------ Data Platform * Build clean, reusable analytical data layers in BigQuery * Move business logic from BI into the warehouse * Define metrics, dimensions, and semantic consistency AI Interaction * Enable reliable AI ↔ data interaction * Design schemas + instructions so AI produces correct outputs * Test and refine real AI usage (not theory) Access & Governance * Implement data-layer access control (not BI-layer) * Row/column-level security, role/attribute-based access * Ensure consistent behavior across BI, AI, and internal tools * Ensure metric reconciliation across different data sources Prevent: * sensitive data leakage * shadow metric layer * uncontrolled query cost Automation: * Replace manual data workflows with AI-driven processes * Build agents for reporting, validation, and internal analytics Experience: Strong SQL + data modeling (BigQuery or similar) * Experience building scalable data layers (not just pipelines) * Understanding of metrics, semantics, and analytical correctness * Hands-on exposure to LLMs / AI tools (practical, not theoretical) * Ability to design systems where data is consumed by machines Bonus experience: * dbt / semantic layers * BigQuery performance & cost optimization * Finance / brokerage data * Fine-grained access control implementations * AI agent / tool-based workflows Why This Role: * You will define how AI uses data in a real business * Work on non-trivial problems (semantics, access, correctness) * Build systems from first principles, not maintain legacy * High ownership The excerpt contains GDPR policy notes and recruitment data retention statements but they are not essential to the job posting.