Software Engineer, Data

# Staff Software Engineer, Data Sift Marina  Del Rey, CA (Hybrid)
Full-time $200,000 – $260,000 / year Upload your resume once and Scout applies for you Apply with Scout Share this job:

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Build a scalable data platform that ingests hardware sensor data and supports real-time reads and large-scale analytics. The role also involves shaping data architecture and engineering practices alongside peers working on streaming and storage systems.
* Permanent* Hybrid
* 7+ years
* Bachelor's Degree### Skills and expertise

Apache Flink Kafka Streams

PostgreSQL Druid Pinot Go Rust Kubernetes ### Key responsibilities
* Design a scalable platform for ingesting millions of hardware sensor data points per second.
* Develop database solutions for real-time reads and large-scale analytics workloads.
* Shape data architecture, engineering standards, and scaling strategies with peers.## How this job compares

Compared with 40 open staff data jobs on October 10, 2026.Pay:
This job pays $200K to $260K a year. The 27 open staff data jobs that publish US pay start at $194K on average, so this job starts in line with them.

Similar open jobs:
We Love AI Jobs lists 40 open staff data jobs at 32 companies.

Remote work:
This job is hybrid. 15 of the 40 staff data jobs (38%) are remote.

AI in this role:
Low. The company works with AI, but AI is a small part of this role's daily work. This role builds streaming and storage infrastructure for hardware telemetry, not AI models or products. The posting’s AI reference is broad company context rather than a stated daily responsibility.## Full description

About Sift Sift is the data infrastructure platform for hardware engineering teams. Sift turns high-frequency telemetry into engineering insights for mission-critical systems. Teams use Sift to build and operate rockets, satellites, autonomous vehicles, energy systems, defense platforms, and more.

Founded by former SpaceX engineers who built the tools behind Dragon and Starlink, Sift is building the data infrastructure to herald the AI era for physical  This Role, You'll:
• Design and build a horizontally scalable platform for ingesting millions of hardware sensor data points per second
• Develop durable, efficient database solutions to support real-time reads and large-scale analytics workloads
• Pioneer data architecture by integrating recent innovations in streaming and storage, including cloud-native and diskless designs
• Help define engineering culture, standards, and processes
• Collaborate closely with peers on architecture, design, code reviews, and scaling strategies

The Skillset You'll Bring:
• Bachelor's degree in Computer Science, Engineering, Physics, or another STEM discipline
• 7+ years of experience in backend, infrastructure, or data engineering roles
• Hands-on experience with event-time-based stream processing or streaming SQL systems using tools like Apache Flink, Kafka Streams, Beam, or similar
• Proficiency with relational and time-series databases like PostgreSQL, Druid, Pinot, Timescale DB, or equivalent
• Experience with large-scale distributed systems or low-latency backend services, ideally written in Go, Rust, or Python
• Familiarity with Dev Ops and cloud infrastructure tools such as Kubernetes, Prometheus, ArgoCD, and Terraform
• Strong communication skills and a collaborative approach to problem-solving

Bonus Points:

• Familiarity with telemetry data from hardware systems, high-throughput ingest pipelines, or columnar storage formats like Apache Arrow and Parquet
• Experience building resilient, performant systems that scale to billions of records
• Curiosity about new data paradigms and eagerness to evaluate and integrate emerging tools and techniques

Engineering at SIFT:

You’ll join a tight-knit team of…