Job Summary

DataPelago is at the forefront of revolutionizing data processing for traditional analytics and cutting-edge GenAI preprocessing. We are building an innovative data processing engine that is transforming how Apache Spark, Apache Flink, Ray and others operate on diverse, large-scale data. Our team of engineers drive and adopt advances in hardware-accelerated computing, parallel processing of large-scale data, query optimization, distributed systems, compilers, machine learning, and cloud-native computing. We are looking for specialists to join our engineering team and shape the future of accelerated data processing.

DataPelago Nucleus is a universal data processing engine that is designed to accelerate the processing of diverse data – structured through unstructured – with any parallel processing framework – e.g., Apache Spark – on any infrastructure – including vectorized CPU and GPU. DataPelago Accelerator for Spark (DPA-S), our product based on DataPelago Nucleus, is running large-scale production applications of many globally renowned customers.

The Opportunity:

As a Senior/Principal Data Processing Optimization Engineer, you will be a key individual contributor in advancing planner and optimization capabilities so that DataPelago acceleration delivers the most performance and cost reduction for open-source software SQL and Python processing engines running on CPU-based and GPU-based infrastructure. This is a unique opportunity to make a significant impact on a category-defining product and work with a talented team of engineers.

What You'll Do:

• Research, design, implement, and deliver logical and physical query plan optimization techniques for massively parallel data processing engines. Develop query planning and query optimization techniques that enable industry-leading performance and performance efficiency on execution engines based on heterogeneous accelerated compute elements.
• Integrate DataPelago data processing acceleration and plan optimization capabilities with diverse open-source engines including Apache Spark and Apache Flink.
• Ensure product performance on customers’ real deployment environment and workload.
• Establish metrics for plan quality, workload performance, reliability and lead the team in ensuring these metrics are continuously improved and achieved in customer deployments.
• Provide technical leadership through all phases of product development and post-production support. Own development and support of major components and capabilities.
• Collaborate with other engineering team members and product management in defining product features, architecture, interfaces, and development timelines. Mentor junior team members.

What You'll Bring

• Bachelor’s degree in computer science. Master’s or PhD preferred, especially in areas related to database systems.
• 15+ years of experience developing query planning and query optimization techniques for enterprise data processing software platform. Prefer at least 5+ years of that experience on parallel platforms such as Apache Spark, Presto/Trino, or Apache Flink.
• Deep knowledge of SQL semantics and expertise in SQL processing. Additional Python processing preferred.  Solid understanding of databases, data warehouses, query engines.
• Deep knowledge of query optimization state of the art, from published literature and open-source software. Prefer own open-source contributions and/or publications in this area.
• Solid understanding of the architecture, deployment, and operations of data processing platforms in applications such as data engineering, data preparation, and analytics.
• Demonstrated proficiency in all phases of software development and post-production support of enterprise software or SaaS. Adept in adopting AI effectively.
• Experience owning the definition and delivery of major product capabilities through technical leadership and collaboration spanning multiple teams.
• Strong collaboration and communication skills.