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Software Engineer Data Infrastructure Jobs (NOW HIRING)

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Staff Software Engineer, Data Infrastructure

OR · Remote

$114K - $137K/yr

About You Minimum Qualifications * 10+ years of software engineering experience building and operating data infrastructure or distributed systems at production scale. * Hands-on expertise with modern ...

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Software Engineer Data Infrastructure information

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$44.5K

$129.7K

$177.5K

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

As of Jul 12, 2026, the average yearly pay for software engineer data infrastructure in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

How does a Software Engineer in Data Infrastructure typically collaborate with data scientists and other engineering teams?

As a Software Engineer in Data Infrastructure, you'll frequently work alongside data scientists, analysts, and other engineering teams to ensure that data pipelines and storage systems are reliable, scalable, and efficient. Collaboration often involves translating data requirements into technical solutions, troubleshooting data flow issues, and optimizing infrastructure for both performance and cost. Regular meetings, code reviews, and cross-functional planning sessions are common, allowing you to gain insights from various perspectives and ensure the infrastructure meets the evolving needs of the organization.

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

AspectSoftware Engineer Data InfrastructureData Engineer
Required CredentialsBachelor's in CS or related, often with certifications in cloud or data toolsBachelor's in CS, Data Science, or related; similar certifications
Work EnvironmentDevelops and maintains data infrastructure, collaborates with data teamsBuilds data pipelines, manages data storage and processing systems
Employer & Industry UsageTech companies, data-driven organizations, cloud providersFinance, healthcare, tech firms, any industry with large data needs
Common Search & ComparisonYesYes

Software Engineer Data Infrastructure and Data Engineer roles often overlap in skills and work environment, focusing on building and maintaining data systems. However, Software Engineers Data Infrastructure tend to focus more on the underlying infrastructure and integration, while Data Engineers emphasize data pipeline development and data management. Both roles are essential in data-driven organizations and require similar credentials and industry usage.

What are Software Engineer Data Infrastructure?

Software Engineer Data Infrastructure are professionals who design, build, and maintain the underlying systems and tools that enable organizations to collect, store, process, and analyze large volumes of data efficiently. They work on creating scalable data pipelines, managing databases, and ensuring data reliability and security. Their work supports data scientists, analysts, and business teams by providing robust, high-performance infrastructure for all data-related operations.

What are the key skills and qualifications needed to thrive as a Software Engineer Data Infrastructure, and why are they important?

To thrive as a Software Engineer Data Infrastructure, you need strong programming skills (such as Python, Java, or Scala), a solid understanding of distributed systems, and experience with data modeling and storage solutions, often backed by a degree in computer science or a related field. Familiarity with technologies like Hadoop, Spark, Kafka, SQL/NoSQL databases, and cloud platforms, as well as certifications in cloud or big data, are highly valued. Excellent problem-solving abilities, collaboration, and clear communication distinguish top performers in this role. These skills ensure robust, scalable, and reliable data infrastructure that supports organizational analytics and business goals.
More about Software Engineer Data Infrastructure jobs
What states have the most Software Engineer Data Infrastructure jobs? States with the most job openings for Software Engineer Data Infrastructure jobs include:
What job categories do people searching Software Engineer Data Infrastructure jobs look for? The top searched job categories for Software Engineer Data Infrastructure jobs are:
Software Engineer Data Infrastructure jobs near you
Infographic showing various Software Engineer Data Infrastructure job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $129,716 per year, or $62.4 per hour.
Software Engineer, Data Infrastructure

Software Engineer, Data Infrastructure

Scale AI

Washington, DC • On-site

Full-time

Posted 20 days ago

Scale AI rating

8.1

Company rating: 8.1 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

95th of 209 rated software companies

Job description

Job Summary:
Scale AI is seeking a highly skilled and motivated Mission Software Engineer to join their dynamic Federal Engineering team. In this role, you will architect and build foundational data infrastructure that serves as the brain of a project ecosystem, developing onsite solutions for government customers and ensuring seamless integration with existing workflows.
Responsibilities:
• Architect the Data Ensemble: Design and implement the architecture to ensemble various sources of injected context (deeply structural simulation data, historical game states, and dynamic user inputs) into a unified, highly queryable format optimized for LLM consumption.
• Massive Batch Infrastructure: Build highly scalable, resilient data architectures from scratch. You will optimize for moving, transforming, and processing massive quantities of simulation output data via enormous batch jobs, maintaining the minimal latency required for rapid wargame iterations.
• Complex Data Modeling: Design sophisticated, highly relational data models that accurately represent massive, state-based simulation environments, making them easily interpretable by machine learning models.
• First-Principles Problem Solving: Navigate highly ambiguous product requirements to design custom, ground-up systems where existing open-source or enterprise tools simply cannot handle the structural complexity or scale.
• Technical Leadership: Set the technical standard for the data infrastructure team, driving rigorous code quality, system performance, and architectural clarity.
Qualifications:
Required:
• 5+ years of backend or data infrastructure experience, operating at a Senior, Staff, or Principal level.
• Deep, expert-level proficiency in systems languages (e.g., Rust, Go, C++, or highly optimized Python/Java, Spark) and a fundamental understanding of memory management, compute limits, and distributed systems architecture.
• Proven track record of processing massive datasets. You understand how to optimize massive batch jobs and parallel processing across distributed simulation nodes without sacrificing speed.
• You must be an expert in surfacing the right needle from an ocean of hay to feed decision-making engines.
• A strong desire to build robust, foundational technology that supports national security and defense modernization.
Preferred:
• An active Secret or TS/SCI clearance is a nice to have for this role. If you do not have an active clearance, you must be eligible and willing to obtain one.
• Experience with LLM context optimization, vector embeddings, or agentic AI frameworks (e.g., advanced RAG architectures).
• Deep domain experience working with wargaming data, complex systems modeling, or distributed simulation protocols.
• Previous experience in a high-growth, 0-to-1 startup environment.
Company:
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. Founded in 2016, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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