Staff Software Engineer (Data Infrastructure)

Peregrine; San Francisco (CA); On-site; USD 140,000 - 180,000; Full time

Job summary

Deepstreamtech is seeking a Staff Data Infrastructure Engineer to tackle complex challenges in architecting and operating scalable data systems. This role demands a deep passion for data infrastructure, with responsibilities including building real-time data integration platforms and working closely with teams to ensure operational excellence. Candidates should have over 8 years of experience, deep expertise in Apache Iceberg and Spark, and solid programming skills in Python or Scala. Join us to make impactful decisions with large volumes of operational data.

Qualifications

• 8+ years of experience in large-scale data infrastructure systems.
• Deep expertise with Apache Iceberg including schema evolution and partitioning strategies.
• Strong software engineering skills with production-quality code.

Responsibilities

• Design and operate high-throughput data integration platforms.
• Architect a scalable open table format layer for data storage.
• Build and optimize distributed data processing pipelines.

Skills

Architecting data infrastructure systems

Apache Iceberg

Apache Spark

Real-time data integration

Data pipeline orchestration

AWS

Kubernetes

Python

Scala

Education

Degree in Computer Science, Engineering, or related field

Tools

Airflow

Apache Kafka

Job description

Requirements

• 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
• 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
• 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

What the job involves

• 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