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Figure

Helix AI Engineer, Data Infrastructure

San Jose, CA · On-site

$150K - $350K/yr

Our Helix team is looking for an experienced Data Infrastructure Engineer, to take our AI data infrastructure to the next level. This role is focused on building tools and software components that ...

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How much do data infrastructure jobs pay per year?

As of Jul 10, 2026, the average yearly pay for data infrastructure in the United States is $123,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,500.00 and $156,000.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior data infrastructure engineers, especially those with extensive experience, expertise in cloud platforms, and advanced skills in data architecture and distributed systems, can earn $500,000 or more annually. High compensation often involves working in large tech companies, leading complex projects, or holding executive-level roles such as Director or VP of Data Infrastructure.

What are some typical challenges faced in a Data Infrastructure role and how are they addressed?

Professionals in Data Infrastructure often face challenges such as scaling systems to handle growing data volumes, ensuring data security, and maintaining high availability. Addressing these requires proactive system monitoring, automation, regular performance tuning, and implementing best practices for backup and disaster recovery. Collaboration with data engineering, analytics, and IT security teams is essential to resolve bottlenecks and optimize data flows. Staying current with emerging technologies also helps in innovating and improving existing infrastructure over time.

What does a data infrastructure engineer do?

A data infrastructure engineer designs, builds, and maintains the systems and tools that store, process, and manage large volumes of data. They work with technologies like cloud platforms, databases, and data pipelines to ensure data is accessible, reliable, and secure for analytics and business operations.

What is the highest paying data job?

The highest paying data jobs typically include Data Engineering Manager, Data Architect, and Chief Data Officer, with salaries often exceeding $150,000 annually. These roles require advanced skills in data modeling, cloud platforms, and leadership, and they oversee large-scale data infrastructure and strategy.

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

To thrive in Data Infrastructure, you need a solid understanding of data architecture, database management, and distributed systems, often supported by a degree in computer science or a related field. Proficiency with tools such as SQL, Hadoop, Spark, AWS, and certifications like Google Cloud Professional Data Engineer are highly valued. Strong problem-solving abilities, effective teamwork, and clear communication help professionals excel in this collaborative and fast-evolving area. These skills ensure robust, scalable data systems that support reliable analytics and decision-making across the organization.

What is a data infrastructure?

Data infrastructure refers to the collection of hardware, software, networks, and storage systems that support the collection, processing, and storage of data within an organization. Data infrastructure professionals design, implement, and maintain these systems to ensure data availability, security, and efficiency, often using tools like cloud platforms and database management systems.

What is a Data Infrastructure job?

A Data Infrastructure job focuses on designing, building, and maintaining the systems that store, process, and manage data for an organization. This includes databases, data pipelines, cloud storage, and data processing frameworks to ensure efficient data flow and accessibility. Professionals in this role work with technologies like SQL, NoSQL, Hadoop, Spark, and cloud platforms to support data engineers, analysts, and scientists. The goal is to provide a scalable, reliable, and secure foundation for handling large volumes of data.

More about Data Infrastructure jobs
What cities are hiring for Data Infrastructure jobs? Cities with the most Data Infrastructure job openings:
What are the most commonly searched types of Data Infrastructure jobs? The most popular types of Data Infrastructure jobs are:
What states have the most Data Infrastructure jobs? States with the most job openings for Data Infrastructure jobs include:
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Data Infrastructure jobs near you
Infographic showing various Data Infrastructure job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $123,312 per year, or $59.3 per hour.
Helix AI Engineer, Data Infrastructure

Helix AI Engineer, Data Infrastructure

Figure

San Jose, CA • On-site

$150K - $350K/yr

Full-time

Re-posted 8 days ago

Job description

Figure is an AI Robotics company developing a general purpose humanoid. Our humanoid robot is designed for commercial tasks and the home. We are based in San Jose and require 5 days/week in-office collaboration. It's time to build.
Figure's vision is to deploy autonomous humanoids at a global scale. Our Helix team is looking for an experienced Data Infrastructure Engineer, to take our AI data infrastructure to the next level. This role is focused on building tools and software components that offload, store, manipulate and provide access to robot data, managing on premise and cloud resources, and providing production support for this infrastructure. The ideal candidate has experience building tools and infrastructure for a large-scale autonomous / deep learning system.
Responsibilities
  • Design, build, and maintain tools and software components that offload, store, manipulate and provide access to robot data
  • Architect and manage storage and compute resources across on-premise and cloud environments at a massive scale.
  • Implement optimal data transmission and storage solutions for all stages of Figure's data pipeline from recording to neural network training
  • Work together with AI researchers to support new kinds of data workflows

Requirements
  • Strong software engineering fundamentals
  • Bachelor's or Master's degree in Computer Science, Robotics, Engineering, or a related field
  • Minimum of 4 years of professional, full-time experience building reliable backend systems
  • Experience with Linux and command line tools
  • Experience with Python
  • Experience using and managing data stores (Postgres, MySQL, ElasticSearch, Redis, etc.).

Bonus Qualifications
  • Experience managing cloud infrastructure (AWS, Azure, GCP)
  • Experience with job scheduling / orchestration tools (SLURM, Kubernetes, LSF, etc.)
  • Experience with configuration management tools (Ansible, Terraform, Puppet, Chef, etc.)
  • Experience building data annotation and dataset management tools.

The US base salary range for this full-time position is between $150,000 - $350,000 annually.
The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.

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