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.
The Foundations team consists of detail-oriented engineers driving innovation and enhancing performance through technical excellence and a focus on results. We own the performance and reliability of key pieces of Peregrine’s infrastructure and take on hard technical problems that create new capabilities for the platform.
We value both ownership and collaboration. You will take full responsibility for the features you own 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.
As a member of our Foundations team, you’ll independently own well-scoped, meaningful projects that improve the reliability and performance of Peregrine’s data platform; the systems that ingest, process, and enrich large volumes of customer data from a wide variety of sources, at high scale and low latency. You’ll work within our datastores, orchestrated data pipelines, and the connection, authorization, and notification layers that keep the entire system efficient and secure — extending existing architectural patterns and proposing new ones where they’re needed.
You’ll take on real technical challenges that meaningfully improve the quality, stability, or velocity of the team. Representative recent work at this level includes:
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Contributing to a rewrite of a core datastore’s underlying storage format and helping roll it out safely across environments
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Upgrading a major framework version within a heavily used service without introducing regressions
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Improving database connection-pooling to reduce outage risk
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Building out a new piece of the platform’s authorization system
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Reducing a data-processing backlog’s latency from hours to under a second
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Helping scale and tune our search infrastructure to keep pace with rapid data growth
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Participating in incident response and root-causing production issues
Our stack is constantly evolving but based on a backend foundation of Python, Django, Celery, Airflow, and Kafka; a frontend built in React, Redux, and Mapbox; data stores including PostgreSQL and Elasticsearch; and AWS, Pulumi, Terraform, and Kubernetes as our underlying infrastructure.