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Data Infrastructure Jobs (NOW HIRING)

WorkBay

Data & Infrastructure Engineer

Draper, UT · On-site

$107K - $128K/yr

Position Overview We are seeking a skilled and motivated Data & Infrastructure Engineer to own and evolve the data platform that powers WorkBay's operations, analytics, and strategic decision-making.

Figma

Software Engineer, Data Infrastructure

San Francisco, CA · On-site +1

$134K - $162K/yr

In the coming years, we're focused on building the data infrastructure layer for Figma's AI-powered products, driving cost and performance optimizations across our data stack, scaling our ingestion ...

Figma

Software Engineer, Data Infrastructure

San Francisco, CA · On-site

$134K - $162K/yr

In the coming years, we're focused on building the data infrastructure layer for Figma's AI-powered products, driving cost and performance optimizations across our data stack, scaling our ingestion ...

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$123.3K

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How much do data infrastructure jobs pay per year?

As of Jun 18, 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 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 that store, process, and manage large volumes of data. They work with tools like databases, data pipelines, and cloud platforms to ensure data is accessible, reliable, and secure for analytics and business operations.

Who are the big 5 in data centers?

The Big 5 in data centers typically refer to the leading providers: Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform, IBM Cloud, and Oracle Cloud. These companies dominate the cloud infrastructure market and often require data infrastructure professionals to manage and optimize their data center operations, including skills in networking, security, and cloud technologies.

What is the highest paying job in data?

In data infrastructure, senior roles such as Data Engineering Managers, Data Architects, and Chief Data Officers tend to have the highest salaries, often exceeding six figures annually. These positions require advanced technical skills, experience with cloud platforms, and leadership responsibilities.

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 is accessible, secure, and reliable for analysis and decision-making.

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:
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Data Infrastructure jobs near you
Infographic showing various Data Infrastructure job openings in the United States as of June 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $123,312 per year, or $59.3 per hour.
Software Engineer, Data Infrastructure

Software Engineer, Data Infrastructure

Peregrine

San Francisco, CA • On-site

$134K - $162K/yr

Full-time

Posted 7 days ago

Job description

Job Summary:
Peregrine is a company that helps public safety organizations and governments address societal challenges using their AI-enabled platform. They are seeking a Data Infrastructure Engineer to own the data layer and build systems for ingesting, storing, and serving real-time operational data, enabling critical decision-making for their customers.
Responsibilities:
• Designing and operating a high-throughput, real-time data integration platform across diverse customer environments
• Architecting a scalable open table format layer for reliable data storage at petabyte scale
• Building and optimizing distributed data processing pipelines with Apache Spark and adjacent streaming technologies
• Driving performance, reliability, and cost efficiency across the full data infrastructure stack
• Collaborating with platform and product engineering teams to define data contracts, schemas, and integration patterns
• Establishing best practices, tooling, and patterns that raise the quality bar for data infrastructure across the organization
Qualifications:
Required:
• 2-5 years of experience operating large-scale data infrastructure systems in production environments
• Experience with open table formats, particularly Apache Iceberg — including schema evolution, partitioning strategies, compaction, and time travel
• Extensive hands-on experience with Apache Spark for batch and streaming data processing at scale
• Background in real-time data integration and stream processing, leveraging technologies such as Apache Kafka, Apache Flink, or equivalents
• Experience with data pipeline orchestration using Airflow or similar tools
• Strong software engineering fundamentals in Python and/or Scala, with a track record of writing production-quality code
• Experience with AWS or comparable cloud platforms, including S3-based data lake architectures
• Experience with Kubernetes and containerized deployment of data workloads
• Degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• Located in San Francisco and open to working in office
Company:
Context changes everything. Founded in 2018, the company is headquartered in San Francisco, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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