Compute Intelligence Engineer
Build the company’s compute intelligence platform, including warehouse infrastructure, production pipelines, data models, dashboards, and AI-accessible analytics. The role requires 3+ years of data-focused engineering experience, strong Python and SQL skills, and cross-functional business judgment.
About the job
Responsibilities
Build the Compute Intelligence Platform
- Stand up the company’s data warehouse and pipelines for compute telemetry, billing and usage data, partner and supply data, CRM, and financial systems.
- Build data models and transformations that create a clean, queryable, trustworthy source of truth.
- Build dashboards and reporting for compute supply, demand, utilization, upcoming capacity, and bottlenecks.
- Create an AI-accessible, queryable layer so teams can answer questions without relying on a data analyst.
Supply and Demand Intelligence
- Track compute supply end to end, including owned, committed, upcoming, utilized, and idle capacity.
- Develop models and views that surface bottlenecks and clarify upcoming supply.
- Connect supply data to demand signals, capacity planning, sales, and research needs.
Cross-Functional Enablement
- Serve as the data backbone for Compute Partnerships, Growth, and Research.
- Partner with Growth on upcoming supply and sellable capacity.
- Partner with Compute Partnerships on utilization, commitments, and supply tracking.
- Partner with Research on scaling needs and capacity planning.
Operational Reliability
- Build unattended, synchronized, and fault-tolerant pipelines and systems.
- Establish data quality, documentation, and infrastructure standards.
- Partner with Engineering on shared infrastructure, security, and data standards.
Requirements
- 3–7+ years of experience in data engineering, analytics engineering, GTM/growth engineering, or similar roles delivering business-focused data infrastructure.
- Experience building and maintaining data warehouses and production-quality pipelines.
- Strong Python and SQL skills.
- Experience with data modeling using dbt or an equivalent tool.
- Experience connecting disparate systems through APIs.
- Experience with modern data stack tooling, orchestration, and BI/dashboarding.
- Business judgment and the ability to translate cross-functional needs into scalable systems.
- Familiarity with AI tooling and AI-accessible data layers, including natural-language querying or LLM-powered analytics.
- High ownership and comfort working in ambiguity and speed.
- Experience using LLMs, automation, and programmatic tools to work efficiently.
Nice-to-Haves
- Experience as an early data hire building data infrastructure from scratch.
- Familiarity with GPU economics, compute infrastructure, cloud telemetry, or AI/ML workloads.
- Background in GTM engineering, growth engineering, or revenue/operations data.
- Experience building LLM-powered or natural-language data interfaces.
- Experience with usage-based or consumption-based business models and their data.
Compensation and Benefits
- Cash compensation: $225,000–$300,000, plus meaningful equity.
- Flexible work arrangement, remote or in San Francisco.
- Visa sponsorship and relocation support.
- Professional development budget.
- Team off-sites and conferences.
Skills
Python, SQL, Snowflake, Google Bigquery, Databricks, dbt, Apache Airflow, Dagster, Bi Dashboarding, Data Warehousing, Data Modeling, APIs, Llm Analytics, Cloud Telemetry, Gpu Computing
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