Principal Software Engineer, Connectivity
Safran
JavaScriptPython
Software Engineer, Platform and Data Infrastructure
Galileo 🔭
full-time
Posted on:
Location: California • 🇺🇸 United States
Visit company websiteSalary
💰 $180,000 - $300,000 per year
Job Level
Mid-LevelSenior
Tech Stack
Distributed SystemsGrafanaKafkaKubernetesNoSQLPythonRabbitMQSparkSQL
About the role
- Build and scale core infrastructure – design and optimize distributed systems and APIs that handle millions of real-time queries with low latency and high reliability
- Develop data-intensive systems – work across SQL, NoSQL, time-series, and object stores, ensuring data pipelines and lookups are optimized for throughput and efficiency
- Optimize performance at scale – profile and tune systems for latency, throughput, and cost
- Work on real-time serving systems – design high-throughput caching layers and data lookup services
- Build and extend pub-sub and orchestration frameworks – leverage and improve systems like Kafka, RabbitMQ, and Celery to coordinate workloads and streaming data pipelines
- Design internal developer tooling – create load testing, benchmarking, and performance analysis tools
- Collaborate cross-functionally – partner with product, research, and application engineering teams to support new capabilities, models, and workloads
Requirements
- Experience with large scale distributed systems
- Addressed challenges that come with systems of scale
- Worked on and optimized high throughput traffic on SQL and NoSQL data stores, time-series databases and/or Object stores
- Experience with NoSQL databases and time-series databases
- Worked on real-time high throughput caching systems
- Excellent python programming skills
- Worked with raw-data lookup indexes such as Lucene and/or similar frameworks
- Experience with runtime orchestration and pub-sub frameworks like RabbitMQ, Celery, Kafka
- Built low-latency data lookup APIs
- Done extensive performance optimizations
- Built internal tooling foundations for performance testing, load testing and benchmarking
- Bonus: Experience with time-series or columnar databases (e.g., ClickHouse, TimescaleDB, DuckDB)
- Bonus: Familiarity with distributed query engines or streaming frameworks (Presto, Trino, Flink, Spark Streaming)
- Bonus: Hands-on with container orchestration and scaling systems (Kubernetes, EKS)
- Bonus: Experience building observability and performance tooling (Grafana, OpenTelemetry, flame graphs)
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