Data Engineer, Real-Time Data Platform (Equity)

SpaceX Super Intelligence; Palo Alto (CA); On-site; USD 125,000 - 400,000; Full time

Benefits offered by this job

Equity

Medical coverage

401(k)

Job summary

SpaceXSI is building a comprehensive data platform within the X product engineering team to serve end users and internal groups such as Product, Algorithm, Legal, Finance and Sales. You will own and operate pipelines across realtime and batch workloads, enabling data-driven decisions at scale.

You will work with BigQuery, Trino, ClickHouse for analytics and Flink, Kafka, Spark/Scalding for streaming and batch processing, while ensuring data quality and rapid iteration.

Qualifications

• Hands-on experience in Python, Rust, Scala, Go or Java with data pipelines and distributed systems.
• Experience with realtime and batch data processing tools such as Spark, Kafka, Flink, SQL and versatile storage systems (RMDBs/NoSQL).
• Proven ability to translate product requirements into engineering plans and collaborate with AI/product teams.

Responsibilities

• Design, build, and operate production-grade realtime and batch pipelines ingesting and processing billions of events daily.
• Create shared datasets, fact tables, and internal data products for cross-team analysis and debugging.
• Prototype tooling to automate data workflows, backfills, dashboards, and self-serve data access.
• Ensure data correctness end-to-end with invariants, reconciliations, and root-cause analysis for metric shifts.
• Navigate query engines (BigQuery, Trino, ClickHouse) and streaming/batch frameworks (Flink, Kafka, Spark/Scalding) as needed.
• Collaborate with product and business teams to identify data gaps and prioritize improvements.

Skills

Python

Rust

Scala

Go

Java

Data pipelines

Distributed systems

Tools

Spark

Kafka

Flink

SQL

Job description

SpaceXSI is building a comprehensive data platform within the X product engineering team to serve end users and internal groups such as Product, Algorithm, Legal, Finance and Sales. You will own and operate pipelines across realtime and batch workloads, enabling data-driven decisions at scale.

You will work with BigQuery, Trino, ClickHouse for analytics and Flink, Kafka, Spark/Scalding for streaming and batch processing, while ensuring data quality and rapid iteration.