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Tech Stack
Tools & technologiesBigQuerySQL
About the role
Key responsibilities & impact- Define how data is understood, accessed, and used by AI systems across the company.
- Build clean, reusable analytical data layers in BigQuery.
- Move business logic from BI into the warehouse.
- Define metrics, dimensions, and semantic consistency.
- Enable reliable AI ↔ data interaction.
- Design schemas + instructions so AI produces correct outputs.
- Test and refine real AI usage (not theory).
- Implement data-layer access control (not BI-layer).
- Ensure consistent behavior across BI, AI, and internal tools.
- Ensure metric reconciliation across different data sources.
- Prevent sensitive data leakage and uncontrolled query cost.
- Replace manual data workflows with AI-driven processes.
- Build agents for reporting, validation, and internal analytics.
Requirements
What you’ll need- 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
Benefits
Comp & perks- Competitive salary
- Flexible working hours
- Professional development budget
- Home office setup allowance
- Global team events
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
SQLdata modelingBigQuerydata layersmetricssemanticsanalytical correctnessLLMsdbtaccess control
Soft Skills
design systemsanalytical thinking
