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Data Infrastructure Engineer Jobs (NOW HIRING)

Slack

Staff Software Engineer, Data Infrastructure

Seattle, WA · On-site

$130K - $156K/yr

Slack is looking for a Staff Software Engineer to join the Data Infrastructure team, responsible for building secure and scalable infrastructure powering Slack's data ecosystem and supporting data ...

Stellic

Lead Data Infrastructure Engineer

San Mateo, CA · On-site

$230K - $260K/yr

Stellic is growing! We're looking for a Lead Data Engineer to own the next phase of our data ... Infrastructure: Terraform * Data transforms: dbt * Orchestration: MWAA / Airflow * Storage: S3 ...

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All JobsData Infrastructure Engineer Jobs

Data Infrastructure Engineer information

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$46.5K

$127.1K

$182K

How much do data infrastructure engineer jobs pay per year?

As of Jun 10, 2026, the average yearly pay for data infrastructure engineer in the United States is $127,066.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $141,000.00 per year, depending on experience, location, and employer.

What is a Data Infrastructure Engineer?

A Data Infrastructure Engineer is a professional who designs, builds, and maintains the systems and architecture that store, process, and manage large volumes of data for organizations. They focus on creating scalable and reliable data pipelines, ensuring data is accessible and secure, and integrating data from various sources. Their work enables data scientists, analysts, and other stakeholders to efficiently use data for decision-making and analytics. Data Infrastructure Engineers often work with tools like Hadoop, Spark, and cloud platforms, and play a critical role in supporting modern data-driven businesses.

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

To thrive as a Data Infrastructure Engineer, you need a solid background in computer science, experience with database management, and expertise in building and optimizing data pipelines, often supported by a relevant degree. Familiarity with tools and platforms like Hadoop, Spark, SQL, cloud services (AWS, Azure, GCP), and containerization technologies such as Docker and Kubernetes is typically required, alongside certifications in cloud or database technologies. Strong problem-solving skills, attention to detail, and effective communication help you collaborate with cross-functional teams and resolve complex technical challenges. These skills and qualities are crucial for ensuring reliable, scalable, and efficient data systems that support business analytics and decision-making.

What are some typical challenges Data Infrastructure Engineers face when scaling systems to handle increased data volume?

Data Infrastructure Engineers often encounter challenges such as ensuring data pipelines remain reliable and performant as data volume grows. This includes optimizing storage solutions, managing distributed systems, and automating data ingestion and transformation processes. Collaborating closely with data scientists and analysts is key to understanding evolving data requirements and proactively addressing potential bottlenecks. Staying updated with the latest tools and best practices helps engineers build scalable, fault-tolerant infrastructure that supports organizational growth.

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

AspectData Infrastructure EngineerData Engineer
Primary FocusBuilding and maintaining data infrastructure, pipelines, and storage systemsDesigning, developing, and optimizing data pipelines and models
Skills & CertificationsCloud platforms, data storage, ETL tools, scriptingSQL, Python, Spark, Hadoop, data modeling
Work EnvironmentData teams, infrastructure teams, cloud environmentsData teams, analytics teams, software engineering
Industry UsageTech, finance, healthcare, any data-driven industryTech, finance, retail, analytics-focused companies

While both roles involve working with data pipelines, Data Infrastructure Engineers focus on building and maintaining the underlying data systems and infrastructure, ensuring data availability and reliability. Data Engineers primarily develop and optimize data pipelines and models for analysis and machine learning. Both roles often collaborate but serve different aspects of data management.

More about Data Infrastructure Engineer jobs
What cities are hiring for Data Infrastructure Engineer jobs? Cities with the most Data Infrastructure Engineer job openings:
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Data Infrastructure Engineer jobs near you
Infographic showing various Data Infrastructure Engineer job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 98% Full Time, and 1% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $127,066 per year, or $61.1 per hour.
Staff Software Engineer, Data Infrastructure

Staff Software Engineer, Data Infrastructure

Peregrine Technologies

New York, NY • On-site

$200K - $275K/yr

Full-time

Posted 27 days ago

Job description

Backed by leading Silicon Valley investors, Peregrine helps public safety organizations, state and local and governments, federal agencies, and private-sector institutions address society's challenges with unprecedented speed and accuracy. Our AI-enabled platform turns siloed and disconnected data into operational intelligence - instantly surfacing mission-critical information to empower better, faster decisions that improve outcomes at every touchpoint. Today Peregrine supports hundreds of customers across 30+ states and two countries, serving more than 125 million people - and we're amplifying our impact as we expand into the enterprise and internationally.
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)
Peregrine Technologies is committed to creating an inclusive environment for all employees. We celebrate diversity and are a proud equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

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