Builds and scales large-scale data infrastructure including batch systems with Spark and Ray Data, streaming pipelines with Kafka/Flink, and storage on S3/Iceberg. Requires deep hands-on experience with production data pipelines and performance debugging.
Salary not listed
On-siteData Engineering
About the role
What we're looking for
We’re looking for someone who has built real systems at scale and cares about correctness, cost, and ergonomics.
Strong signals include:
Deep experience with Spark (Databricks or open-source Spark both count)
Production experience with Ray Data
Hands-on ownership of large data pipelines and storage systems
Comfort debugging performance issues across compute, storage, and networking layers
Clear thinking about data modeling and long-term maintainability
Nice to have
Experience running or scaling ClickHouse
Familiarity with dbt, Dagster, or similar orchestration and modeling tools
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