Distributed Data Platform Engineer - Real-Time Pipelines

Maxxd; Palo Alto, Northern (CA, KY); Hybrid; USD 180,000 - 440,000; Full time

Benefits offered by this job

Equity

Medical insurance

Vision insurance

Dental insurance

401(k) retirement plan

Disability insurance

Life insurance

Discounts and perks

Job summary

SpaceXAI is seeking a software engineer for the Data Platform team. You will design, build, and operate distributed systems powering SpaceXAI's data movement and compute.

You will own infrastructure components that process trillions of events daily, driving scalability, reliability, and performance across product and ML workloads. Collaborate with ML, product, and infrastructure teams to unblock critical data workflows, optimize Kafka, Spark, Flink, and Trino pipelines, and ship robust,

Qualifications

• Proficiency in Rust, Go, Scala or similar systems languages.
• Hands-on experience with Kafka, Flink, Spark, Trino, or Hadoop in production.
• Strong debugging, profiling, and performance optimization skills.
• Track record of shipping and maintaining critical infrastructure.
• Comfortable working in fast-moving, high-stakes environments with minimal guardrails.

Responsibilities

• Design and implement high‑throughput, low‑latency data ingestion and transport systems.
• Scale and optimize multi‑tenant Kafka infrastructure supporting real‑time workloads.
• Extend and tune Spark, Flink, and Trino for demanding production pipelines.
• Build interfaces, APIs, and pipelines enabling teams to query, process, and move data at petabyte scale.
• Debug and optimize distributed systems, with a focus on reliability and performance under load.
• Collaborate with ML, product, and infrastructure teams to unblock critical data workflows.

Skills

Rust

Go

Scala

Tools

Kafka

Flink

Spark

Trino

Hadoop

Job description

SpaceXAI is seeking a software engineer for the Data Platform team. You will design, build, and operate distributed systems powering SpaceXAI's data movement and compute.

You will own infrastructure components that process trillions of events daily, driving scalability, reliability, and performance across product and ML workloads. Collaborate with ML, product, and infrastructure teams to unblock critical data workflows, optimize Kafka, Spark, Flink, and Trino pipelines, and ship robust,