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Salary: USD 200,000 - 275,000 / annual
Peregrine Technologies is seeking a Staff Software Engineer for Data Infrastructure to architect and operate the foundational data systems that power the company's AI-enabled platform for public safety and government agencies. This is a senior individual contributor role with deep ownership over the data layer handling massive volumes of real-time operational data across 30+ states and two countries.
Key responsibilities include 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 using Apache Spark and streaming technologies; driving performance, reliability, and cost efficiency across the full data infrastructure stack; collaborating with platform and product teams to define data contracts and integration patterns; and establishing best practices and tooling that raise quality standards across the organization.
The technical stack includes AWS GovCloud, Apache Iceberg, Apache Spark, Apache Kafka, Airflow, and Kubernetes. The role requires 8+ years architecting and operating large-scale data infrastructure in production; deep expertise with Apache Iceberg including schema evolution, partitioning, compaction, and time travel; extensive hands-on experience with Spark for batch and streaming; strong background in real-time data integration with Kafka, Flink, or equivalents; experience with Airflow or similar orchestration tools; production-quality coding in Python and/or Scala; extensive AWS or comparable cloud platform experience including S3-based data lakes; Kubernetes and containerized deployment experience; and a CS/Engineering degree or equivalent.
The team values empathy, ownership, collaboration, humility, and perseverance. Engineers work closely with deployment teams and users to understand use cases and iterate on solutions. This is an opportunity to shape foundational infrastructure decisions and tackle complex, ambiguous technical problems at scale.
