Summary

This role sits at the frontier of how AI consumes and acts on internal company data. You'll be the data layer for the entire company — a strategic partner to Finance, Marketing, Sales, Product, and Data Science — designing the clean, trusted datasets that power our AI tooling and ensuring every team can make decisions from a single source of truth. You'll explore how technologies like MCP can unlock self-serve AI data access across the org, and ensure that as we adopt new AI capabilities, our data is ready to meet them. The rest of the company's AI ambitions run through you.

What You'll Do:

1. Build and own the canonical data models in Snowflake that serve as Alchemy's company-wide source of truth — clean, queryable, and AI-ready
2. Structure datasets so vendor AI tools perform optimally out of the box, with consistent schemas, rich semantics, and well-indexed access patterns
3. Explore and prototype MCP integrations that let internal teams query data conversationally 
4. Eliminate shadow tables and one-off datasets by proactively serving team data needs at the platform level, freeing data science to move faster
5. Own the transformation layer (dbt), with rigorous testing and validation so every downstream consumer — human or AI — can trust what they're working with

What We're Looking For:

1. 6+ years in data engineering with strong SQL and deep Snowflake expertise
2. Experience designing efficient, scalable analytical data models
3. Proficiency with dbt or comparable transformation frameworks
4. Strong data quality instincts and a track record of building infrastructure that unblocks teams
5. Good judgment — you scope well, prioritize ruthlessly, and communicate tradeoffs
6. Experience in startups, a plus

Skills

• Analytical Thinking
• Communications Skills
• Database Management
• Software Engineering
• SQL
• Team Collaboration