Data Analytics Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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Relocation assistance

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work

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Application

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Deadline

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About this role

Data Analytics Engineer San Francisco | Hybrid | New York | Remote 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. What You'll Do: - 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 - 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 What We're Looking For: - 6+ years in data engineering with strong SQL and deep Snowflake expertise - Experience designing efficient, scalable analytical data

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