ZipRecruiter

Log In

1

Software Engineer Data Infrastructure Jobs (NOW HIRING)

CoreWeave

Software Engineer - Data Infrastructure Services

$117K - $140K/yr

... data protection regulation. Qualifications : Required : • 2~5 years of experience in a software or infrastructure engineering industry. • Experience operating services in production and at scale ...

previous page

Showing results 41-60

All JobsTechnology JobsNetworking JobsNetwork Engineer JobsSoftware Engineer Data Infrastructure Jobs

Software Engineer Data Infrastructure information

See salary details

$44.5K

$129.7K

$177.5K

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

As of Aug 22, 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.

What is a 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.

How does a software engineer 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 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.

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.

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 August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Staff Software Engineer, Data Infrastructure

Peregrine Technologies

San Francisco, CA • On-site

$200K - $275K/yr

Full-time

Re-posted 12 days ago

Job description

Team

As an engineering team, we believe strongly that empathy improves our solutions. Seeing how people use the product is a priority and the way we get to the right answer. Engineers will have the opportunity to work closely with our team onsite to understand the variety of use cases that Peregrine serves.

We value both ownership and collaboration-you will take full responsibility for major features and work closely with other engineers to drive them to completion. We believe that humility and empathy are essential for building the right solutions-you will collaborate directly with our deployment team and users as we iterate to solve their problems. Perseverance and creativity are crucial to executing our vision.

Role

We are looking for a Staff Data Infrastructure Engineer to join our growing team, where you will have deep ownership over the data layer that underpins everything Peregrine does. You will architect and build the systems that ingest, store, and serve massive volumes of real-time operational data - enabling our customers to make critical decisions with speed and confidence.

This is a senior individual contributor role for someone who thrives on hard technical problems and brings the experience and judgment to shape foundational infrastructure decisions. You will tackle a wide range of complex challenges, including:

  • 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

Our stack is constantly evolving but is built on AWS GovCloud, Apache Iceberg, Apache Spark, Apache Kafka, Airflow, Kubernetes, and more.

About You
  • Deep passion for data infrastructure - you care about building systems that are correct, fast, and resilient at scale
  • Thrive on ambiguity and are energized by defining the right solution to hard, open-ended problems
  • Strong technical vision with the ability to translate complex data requirements into clean, durable infrastructure designs
  • Desire to own significant portions of the data stack end-to-end, from ingestion to serving
  • Committed to operational excellence - you build things you're proud to operate
What We Look For
  • 8+ years of experience architecting and operating large-scale data infrastructure systems in production environments
  • Deep expertise 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
  • Strong background in real-time data integration and stream processing, leveraging technologies such as Apache Kafka, Apache Flink, or equivalents
  • Solid 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
  • Extensive 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, New York, or Washington DC and open to working in office

Salary Range: $200,000 - $275,000 Annually + Benefits + Equity (if applicable) + Bonus (if applicable)

Apply