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 Annual Salary + Benefits + Equity (if applicable) + Bonus (if applicable) $200,000 — $275,000 USD Actual compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, certifications or licenses, and specific work location. Information on the benefits offered is here . 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.

Requirements

Must-haves

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.
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

Nice-to-haves

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Keywords to mirror

aiawskubernetespython

Platform: greenhouse
Effort: quick

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