Data Analytics Engineer

Alchemy•San Francisco, CA

5d•$200,000 - $240,000

About The Position

Our mission is to bring web3 to a billion people, by providing builders with the tools they need to build exceptional onchain products. Alchemy is the only complete developer platform that offers the powerful APIs, SDKs, and tools necessary to build and scale onchain apps and rollups. Our infrastructure powers 70% of the top web3 teams, 90%+ of web2 companies building in web3 and 100+ million end users. Our customers include top web3 brands like Polymarket, OpenSea, Circle, WorldCoin, as well as major global brands like Shopify and Adobe. The Alchemy team draws from decades of deep expertise in massively scalable infrastructure, AI, and blockchain from leadership roles at leading companies and universities like Google, Microsoft, Facebook, Stanford, and MIT. We're backed by the world's leading VCs and institutions, including: Lightspeed, Silver Lake, a16z, Coatue, Pantera, Addition, Stanford University, Coinbase, and Charles Schwab, among others. The Role 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.

Requirements

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

Nice To Haves

Experience in startups, a plus

Responsibilities

Build and own the canonical data models in Snowflake that serve as Alchemy's company-wide source of truth — clean, queryable, and AI-ready
Structure datasets so vendor AI tools perform optimally out of the box, with consistent schemas, rich semantics, and well-indexed access patterns
Explore and prototype MCP integrations that let internal teams query data conversationally — no SQL required
Eliminate shadow tables and one-off datasets by proactively serving team data needs at the platform level, freeing data science to move faster
Own the transformation layer (dbt), with rigorous testing and validation so every downstream consumer — human or AI — can trust what they're working with