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Tech Stack
Tools & technologiesApacheDistributed SystemsHadoopJavaPyTorchRayRustScalaSparkC++
About the role
Key responsibilities & impact- Design and maintain efficient distributed Lance dataset operations
- Build efficient indices to enable predicate pushdown and accelerate queries in Spark, Ray, or Trino
- Work on table formats, data encodings, and various aspects of the Lance format in Rust
- Drive open-source community efforts to integrate the Lance format with Spark, Hive Metastore, Presto, Trino, Ray, and other data infrastructure systems
- Operate and improve internal data processing infrastructure
- Promote the Lance format in open-source communities and at Big Data conferences
- Contribute scale and performance improvements, integrations with the wider data and AI ecosystem, simplified distributed operations, and usability and maintainability enhancements
Requirements
What you’ll need- 10+ years of experience building high-performance databases, big data systems, or large-scale data services
- Deep understanding of internals of open-source Big Data or AI training systems (e.g., Hadoop, Spark, Flink, Ray, Iceberg, Delta Lake, Hudi, ClickHouse, Trino, Presto, PyTorch, or JAX)
- Strong experience with high-performance computing in C++, Java, and/or Scala
- Experience with Rust or willingness to learn it
- Ability to move fast, work independently, and collaborate with a high-caliber team
- Contributor, committer, or PMC member in Apache or other large open-source projects
- Experience with Apache Arrow, DataFusion, Parquet, Iceberg, or Delta Lake
- Track record of driving large features or integrations in distributed systems
- Strong community presence and passion for open-source collaboration
Benefits
Comp & perks- Equity grants
- Medical, dental, vision, and life insurance
- 401(k) retirement plan
- Flexible Spending Accounts (FSA) and Health Savings Accounts (HSA)
- Commuter benefits
- Generous paid time off
- Paid parental leave program for birthing, non-birthing, adoptive, and foster parents
