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Big Data Infrastructure Engineer Jobs in California

Droyd

Data Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

They are seeking a Staff Software Engineer on data infrastructure to own the pipelines that carry ... is a big plus • Strong sense of ownership and can drive complex systems end to end • ...

HeyGen

Data Infrastructure Engineer

Los Angeles, CA · On-site

$115K - $151K/yr

As a Data Infrastructure Engineer, you will lead the development of fundamental data systems and infrastructure. These systems are essential for powering our innovative applications, including Avatar ...

Droyd

Data Infrastructure Engineer

San Francisco, CA · On-site

$134K - $162K/yr

About the role As a Staff Software Engineer on data infrastructure at Droyd, you'll own the ... Is proficient in Rust, Go, or Python -- Rust is a big plus * Has a strong sense of ownership and ...

Alljoined

Data Infrastructure Engineer

San Francisco, CA · On-site

$140K - $180K/yr

About the Role As a Data Infrastructure Engineer , you will build the backend and hardware architecture that allows us to do high-quality and fast research. You'll be owning our entire data lifecycle ...

Pivot Robotics

Data Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

Build and maintain data infrastructure on AWS * Build the artifact store for scans, meshes, model checkpoints, and calibration files * Build edge-to-cloud pipelines between robotic cells and our ...

Pivot Robotics

Data Infrastructure Engineer

San Francisco, CA · On-site

$126K - $166K/yr

Build and maintain data infrastructure on AWS * Build the artifact store for scans, meshes, model checkpoints, and calibration files * Build edge-to-cloud pipelines between robotic cells and our ...

NetApp

Intelligent Data Infrastructure Engineer

San Jose, CA · On-site

$202K - $239K/yr

Job Summary We are seeking an Intelligent Data Infrastructure Engineer to design, develop, and optimize the core software that powers next-generation data infrastructure for enterprise and AI ...

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Big Data Infrastructure Engineer information

See California salary details

$45.9K

$125.4K

$179.6K

How much do big data infrastructure engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for big data infrastructure engineer in California is $125,402.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,100.00 and $139,200.00 per year, depending on experience, location, and employer.

What is a big data infrastructure engineer?

Big Data Infrastructure Engineers are IT professionals responsible for designing, building, and maintaining the systems and environments that process and store large volumes of data. They work with technologies such as Hadoop, Spark, and cloud platforms to ensure data pipelines are efficient, scalable, and reliable. These engineers also manage data storage, security, and high-performance computing resources, enabling organizations to analyze and leverage big data for business insights.

What are the key skills and qualifications needed to thrive as a big data infrastructure engineer?

To thrive as a Big Data Infrastructure Engineer, you need expertise in distributed systems, data architecture, and programming languages like Java, Scala, or Python, typically backed by a relevant degree in computer science or engineering. Proficiency with big data tools such as Hadoop, Spark, Kafka, and experience with cloud platforms (AWS, Azure, or GCP) and containerization technologies are crucial, as are certifications in these areas. Strong problem-solving, teamwork, and communication skills set top performers apart in this role. These skills enable efficient design, deployment, and maintenance of scalable data systems that support business intelligence and analytics needs.

What are some common challenges big data infrastructure engineers face when ensuring system scalability and reliability?

Big Data Infrastructure Engineers often encounter challenges related to optimizing system performance as data volumes grow rapidly. Ensuring that the infrastructure can scale horizontally without downtime requires careful planning and implementation of distributed computing frameworks. Additionally, maintaining data integrity and fault tolerance in complex, multi-node environments can be demanding, requiring constant monitoring and quick responses to system failures. Collaborating closely with data engineers and DevOps teams is essential to proactively address these challenges and implement robust solutions.

What is the difference between Big Data Infrastructure Engineer vs Data Engineer?

AspectBig Data Infrastructure EngineerData Engineer
Primary FocusDesigning, building, and maintaining big data infrastructure and pipelinesDeveloping and managing data pipelines, databases, and data models
Skills & CertificationsHadoop, Spark, cloud platforms, Linux, scriptingSQL, Python, ETL tools, cloud services
Work EnvironmentData centers, cloud environments, big data platformsData warehouses, cloud platforms, analytics teams
Industry UsageTech, finance, healthcare, any data-heavy industryTech, finance, retail, analytics-focused companies

While both roles involve working with data, Big Data Infrastructure Engineers focus on building and maintaining the infrastructure for processing large datasets, whereas Data Engineers develop data pipelines and models to enable data analysis. Understanding these distinctions helps in choosing the right career path or job search focus.

Data Infrastructure Engineer

San Francisco, CA • On-site

Droyd
See more jobs at Droydexternal

$126K - $166K/yr

Full-time

Re-posted 2 days ago

Job description

Job Summary:
Droyd is a company that builds autonomous robotic systems to automate manual work for enterprises. They are seeking a Staff Software Engineer on data infrastructure to own the pipelines that carry data from robot to model, architecting ingestion from edge devices and ensuring fleet data is immediately usable for training and evaluation.
Responsibilities:
• Architect, build, and maintain highly-available data pipelines for robot video, telemetry, and demonstration data
• Own the path from robot to training set: edge ingestion, MoQ/WebTransport streaming, storage, indexing, and retrieval
• Work with ML and robotics engineers to make fleet data immediately usable for training and evaluation
• Improve throughput, reliability, and cost across the full data path
• Build tooling that lets the team find, inspect, and trust the data
• Help set technical direction for data and infrastructure as the fleet scales
Qualifications:
Required:
• 5+ years of software development experience
• Hands-on experience architecting and optimizing large-scale data pipelines
• Proficient in Rust, Go, or Python — Rust is a big plus
• Strong sense of ownership and can drive complex systems end to end
• Communicates clearly and works well with ML, robotics, and hardware engineers
Preferred:
• Experience with streaming video, telemetry-heavy systems, or robotics/edge data
Company:
SaaS, Report Automation, Communication Founded in 2020, the company is headquartered in Paris, FRA, with a team of 2-10 employees. The company is currently Early Stage.

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