About the role

Role overview

Join Sift as a Staff Software Engineer (Data) to help define the core architecture and scale a real-time telemetry platform. You’ll design backend systems for large-scale ingest and develop data/streaming architecture alongside a highly collaborative engineering team.

Responsibilities

Define core architecture and help scale a real-time telemetry platform from the ground up
Design and build a horizontally scalable platform for ingesting millions of sensor data points per second
Collaborate with peers on architecture, design, code reviews, and scaling strategies
Contribute to engineering culture, standards, and processes

Requirements

Strong proficiency with relational and time-series databases, e.g. PostgreSQL, Druid, Pinot, TimescaleDB (or equivalent)
Familiarity with DevOps and cloud infrastructure, e.g. Kubernetes, Prometheus, ArgoCD, Terraform
Experience with large-scale distributed systems or low-latency backend services, ideally in Go, Rust, or Python
7+ years of experience in backend, infrastructure, or data engineering roles
Experience building resilient, high-performance systems that scale to billions of records
Hands-on experience with event-time stream processing or streaming SQL using Apache Flink, Kafka Streams, Beam, or similar
Strong communication skills and a collaborative problem-solving approach
STEM Bachelor’s degree (Computer Science/Engineering/Physics or related)

Nice-to-haves

Domain familiarity with hardware telemetry and high-throughput ingest pipelines
Experience with columnar storage formats like Apache Arrow and Parquet
Interest in emerging data paradigms and evaluating new tools/techniques

About Sift

Sift builds technology platforms focused on real-time telemetry and data infrastructure. The role suggests work on backend systems and scalable data pipelines for high-throughput hardware sensor data.