Compute Intelligence Engineer

What you'll do

• Build the data warehouse, pipelines, models, and dashboards that provide a shared source of truth for compute and related business data.
• Connect compute supply data to demand signals and enable teams to plan capacity, utilization, commitments, and growth.
• Create reliable, documented data systems and an AI-accessible query layer for cross-functional self-service.

What they ask for

• 3–7+ years in data engineering, analytics engineering, GTM/growth engineering, or similar roles building data infrastructure for business outcomes.
• Production-quality pipeline skills in Python and SQL, data warehouse experience, data modeling with dbt or equivalent, and experience connecting systems via APIs.
• Experience with modern data stack tooling, such as Snowflake, BigQuery, or Databricks; orchestration tools; and BI/dashboarding tools.
• Familiarity with modern AI tooling and interest in AI-accessible data layers; uses LLMs, automation, and programmatic tools in their work.

Nice to have

• Early data-hire experience building company data infrastructure from scratch.
• Familiarity with GPU economics, compute infrastructure, cloud telemetry, AI/ML workloads, GTM or revenue operations data, LLM-powered data interfaces, or usage-based business models.

Pay

USD 225-300k base salary

Tools

Snowflake, BigQuery, Databricks, dbt, Airflow, Dagster, Python, SQL

AI focus

Build an AI-accessible data layer, such as natural-language querying or LLM-powered analytics, and use LLMs, automation, and programmatic tools to work faster.