Staff Software Engineer (Data Infrastructure)

• 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
• 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
• 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

Benefits

• Health insurance: Enjoy top-notch health, dental, and vision insurance. Your health matters

• Unlimited PTO: Assume responsibility for how much time you take off. Trust is everything

• Competitive 401k: Leverage a Peregrine-sponsored 401k plan. And think of your future

• Wellness stipend: Use Peregrine’s wellness stipend to focus your body and mind

• HSA: Set aside money to pay for qualified medical expenses with a HSA

• Parental leave: Because we want to support the Peregrine parents out there

• Professional development: Access a range of professional development courses and resources

• Recreational perks: Enjoy a whole host of travel and leisure discounts, and explore new things

• 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

• Deep passion for data infrastructure — you care about building systems that are correct, fast, and resilient at scale

• Desire to own significant portions of the data stack end-to-end, from ingestion to serving

• 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

• Committed to operational excellence — you build things you’re proud to operate

• Strong software engineering fundamentals in Python and/or Scala, with a track record of writing production-quality code

• Deep expertise with open table formats, particularly Apache Iceberg — including schema evolution, partitioning strategies, compaction, and time travel

• 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

• 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

• 8+ years of experience architecting and operating large-scale data infrastructure systems in production environments

• Extensive hands-on experience with Apache Spark for batch and streaming data processing at scale