Database Developer-SQL, Kernel, and Query Optimizer Developer

Location: United States

We are looking for a strong Database Developer who will be responsible for the research, design, and development of advanced features in the query optimizer component of Oracle Database. Additionally, you can be adding autonomous features and self learning and ML capabilities in keeping the query optimizer on the leading edge with respect to the competing database systems.

Our vision is to make Oracle query optimizer the most advanced yet easiest to use in the industry but most importantly continue to have fun achieving it

The team members have a strong research background and strive to bring the most advanced ideas to market in the latest versions of Oracle RDBMS. The group actively participates in collaborative manner of designing cross-group features like data partition pruning, zone map pruning, bloom filtering and pruning, database in-memory costing and optimization, JSON and XML document processing. Our team is heavily involved in the creation of automatic features (e.g. auto SQL plan management, auto indexing, auto error mitigation) for On-Prem databases and Autonomous Database announced by Larry Ellison at the Oracle Open World in Oct 2017. The group actively participates in customer and standard industry benchmark efforts. The group owns a large patent portfolio reflecting the ownership of many state-of-the-art innovations.

Qualifications:

The candidate must have the following:

1. 6+ years of industry experience
2. knowledge of SQL databases
3. knowledge of how SQL is processed by kernel
4. systems programming experience
5. kernel software development

Highly desirable:

1. knowledge of SQL query optimization

About Us

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Optimizer group is responsible for developing Oracle's state of the art query optimizer. The query optimizer is often referred to as the brain of the database management system because it is the component that decides how to process SQL queries by building execution plans. Some of the optimizer areas include automatic statistics gathering, query transformation techniques, search algorithms and cost formulas to select access paths, join methods, join orders to produce the best performing execution plan for a SQL statement. The algorithms for efficient query processing encompass applications and areas like data warehousing, OLTP and non-traditional data processing (e.g. Text, Spatial, XML, JSON).