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Data Compute Jobs in California (NOW HIRING)

FloQast

Engineering Manager, Data Platform

San Jose, CA · On-site

$200 - $250/hr

You'll hold technical authority on data compute and architecture decisions while building the team that executes them -- and you'll do both at the same time, not in phases. What You'll Do As a ...

FloQast

Engineering Manager, Data Platform

San Jose, CA · On-site

$188K - $282K/yr

You'll hold technical authority on data compute and architecture decisions while building the team that executes them -- and you'll do both at the same time, not in phases. What You'll Do As a ...

FloQast

Engineering Manager, Data Platform

San Jose, CA · On-site

$188K - $282K/yr

You'll hold technical authority on data compute and architecture decisions while building the team that executes them - and you'll do both at the same time, not in phases. What You'll Do As a ...

FloQast

Engineering Manager, Data Platform

San Jose, CA · On-site

$188K - $282K/yr

You'll hold technical authority on data compute and architecture decisions while building the team that executes them - and you'll do both at the same time, not in phases. What You'll Do As a ...

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Data Compute information

What is a data compute?

A Data Compute job involves managing and optimizing computational resources for processing large datasets. Professionals in this role work with cloud platforms, distributed computing frameworks, and high-performance computing (HPC) systems to ensure efficient data processing. They collaborate with data engineers and scientists to enhance performance, scalability, and cost-effectiveness of computational workloads.

What does a data compute do?

In a Data Compute role, your daily tasks may include designing and monitoring data pipelines, running large-scale data processing jobs, and maintaining the integrity and performance of compute infrastructure. You'll frequently collaborate with data scientists, engineers, and analysts to ensure datasets are accessible and optimized for analysis. Troubleshooting data processing bottlenecks, implementing automation solutions, and optimizing cloud or on-premises resources are also common aspects of the job. This role involves a mix of hands-on technical work and strategic planning to support data-driven decision-making across the organization.

What are the key skills and qualifications needed to thrive in the data compute position, and why are they important?

To thrive as a Data Compute professional, you need strong analytical abilities, expertise in data processing, and a relevant degree in computer science, statistics, or a related field. Familiarity with big data platforms (such as Hadoop or Spark), programming languages like Python or SQL, and certifications in cloud computing or data analytics are commonly expected. Attention to detail, problem-solving aptitude, and effective communication are crucial soft skills in this position. These skills are vital for ensuring accurate data interpretation, optimizing compute resources, and collaborating efficiently with other teams.

What are popular job titles related to Data Compute jobs in California?

For Data Compute jobs in California, the most frequently searched job titles are:

What job categories do people searching Data Compute jobs in California look for?

The top searched job categories for Data Compute jobs in California are:

What cities in California are hiring for Data Compute jobs?

Cities in California with the most Data Compute job openings:

Data Compute jobs near you
Infographic showing various Data Compute job openings in California as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 15% Part Time, and 5% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Compute Intelligence Engineer

Prime Intellect

San Francisco, CA • On-site

$114K - $157K/yr

Full-time

Re-posted 3 days ago

Job description

Own Your Intelligence
Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.
Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.
Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators - including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.
Your Role
Compute is the foundational input of everything Prime Intellect does - and right now, the picture of our compute supply, demand, and economics lives across spreadsheets, partner conversations, and people's heads. This role changes that.
As Compute Intelligence Engineer, you'll build the data infrastructure and intelligence platform that gives the entire company a live, accurate picture of our compute: what we have, what's coming online, where our bottlenecks are, and how supply maps to demand. This is a hands-on data engineering build - you'll stand up the warehouse, write the pipelines that pull from our compute telemetry, billing systems, partner data, and CRM, model that data into a clean and trustworthy source of truth, and turn it into dashboards and a queryable layer the whole company relies on.
This is a builder-first role with a clear business purpose. You won't be building data infrastructure for its own sake - you'll be building the system that lets our Compute Partnerships team, Growth team, and Research team operate from the same source of truth. When Growth needs to know what capacity is coming online next quarter, when Compute Partnerships needs to understand our utilization against commitments, when Research needs to scale a training run - the platform you build is what they'll turn to.
You'll be early in this seat, and the foundations you lay will be the data backbone the company scales on.
Responsibilities
Build the Compute Intelligence Platform
  • Stand up Prime Intellect's data warehouse (Snowflake, BigQuery, or equivalent) and the pipelines that feed it - compute telemetry, billing and usage data, partner and supply data, CRM, and financial systems
  • Build the data models and transformations (dbt or equivalent) that turn raw data into a clean, queryable, trustworthy source of truth
  • Build dashboards and reporting that give the company a live picture of compute supply, demand, utilization, upcoming capacity, and bottlenecks
  • Build a queryable, AI-accessible layer on top of the warehouse so teams across the company can answer their own questions without going through a data analyst

Supply & Demand Intelligence
  • Build the data systems that track our compute supply end-to-end: what we have, what's committed, what's coming online, and what's utilized vs. idle
  • Develop the views and models that surface where our bottlenecks are - and make upcoming supply legible to the teams that depend on it
  • Connect supply data to demand signals so the company can see, in one place, how capacity maps to what we're selling and building

Cross-Functional Enablement
  • Serve as the data backbone connecting Compute Partnerships, Growth, and Research - building the systems that let them operate from shared, accurate information
  • Partner with Growth on understanding upcoming supply and how it maps to what they can sell
  • Partner with Compute Partnerships on utilization, commitments, and supply tracking
  • Partner with Research on scaling needs and capacity planning

Operational Reliability
  • Build pipelines and systems that run unattended, stay in sync, and fail gracefully
  • Establish the data quality, documentation, and infrastructure standards that let the data layer scale with the company
  • Partner with Engineering on shared infrastructure, security, and data standards

What We're Looking For
  • 3-7+ years in data engineering, analytics engineering, GTM/growth engineering, or similar roles where you've built data infrastructure that served real business outcomes
  • Strong technical skills: comfortable building and maintaining data warehouses, writing production-quality pipelines (Python, SQL), modeling data (dbt or equivalent), and connecting disparate systems via APIs
  • Experience with modern data stack tooling - Snowflake / BigQuery / Databricks, dbt, orchestration (Airflow, Dagster, etc.), and BI/dashboarding tools
  • A builder's instinct paired with business judgment - you don't just build what's asked; you understand the business well enough to build the right thing
  • Comfortable being the data backbone for cross-functional teams - translating between business needs and the systems that serve them
  • Familiarity with modern AI tooling and an interest in building AI-accessible data layers (natural-language querying, LLM-powered analytics) that let non-technical teams self-serve
  • High ownership - you see gaps and build the fix before anyone asks
  • Comfortable in ambiguity and speed; you'll be defining what the data layer looks like from scratch
  • AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster

Bonus:
  • Experience as an early data hire who built a company's 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
  • Working knowledge of usage-based / consumption-based business models and the data they generate

What We Offer
  • Cash Compensation Range of $225-300k + meaningful equity
  • Flexible work (remote or San Francisco)
  • Visa sponsorship and relocation support
  • Professional development budget
  • Team off-sites and conferences
  • A front-row seat to building the infrastructure layer for open AI

Apply