Drive the design and implementation of ESE enhancements that improve scalability, performance, reliability, and storage efficiency. Lead investigations into future storage technologies including QLC SSDs, SMR drives, Zoned Storage, and other emerging storage media. Evaluate storage engine innovations from open-source technologies such as RocksDB, Pebble, WiredTiger, and related ecosystems, identifying opportunities to incorporate proven concepts and techniques into ESE. Develop solutions that reduce write amplification, improve storage endurance, and optimize capacity utilization across large-scale deployments. Advance ESE investments including log write path modernization, lock-free data structures, intelligent caching, write reduction technologies, and next-generation storage optimizations. Prototype, benchmark, and validate new storage architectures and technologies, providing data-driven recommendations for adoption. Serve as a technical leader influencing ESE strategy, architecture, implementation, experimentation, and engineering execution across multiple product teams. Performance analysis and scalability engineering Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++ or C These

requirements include but are not limited to the following specialized security screenings: Master's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 15+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Significant experience developing database engines, storage systems, filesystems, distributed systems, or operating system components. Solid C/C++ systems programming experience. Experience evaluating and integrating external or open source technologies into large-scale production systems. Experience with RocksDB, Pebble, WiredTiger, LevelDB, Cassandra, MySQL/InnoDB, PostgreSQL internals, or similar storage engines. Experience with QLC SSDs, SMR storage, Zoned Storage, NVMe, and emerging storage technologies. Experience benchmarking storage systems and performing workload characterization.

Citus Data scales out PostgreSQL, taking relational power further for real-time applications. The CitusDB database offers a unique combination of massive parallelism, real-time reads/writes, and rich PostgreSQL expressiveness including native support for JSON data. The result is an extensible distributed database with an open ecosystem that powers interactive analytics and operational workloads -- making it simple for organizations to ingest, explore and aggregate billions of events on the fly.

Based in San Francisco, Citus Data is a Y Combinator alumnus and is backed by investors that include Data Collective, Bullpen Capital, and SV Angel. The CitusDB database is used by enterprises across multiple verticals, including e-commerce, retail, security, ad-tech, and mobile analytics, and is available for download from the company’s website at www.citusdata.com.

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