Staff Engineer, Query Optimization

About the role

You will join the MongoDB Server Query Optimization team and help build a world-class distributed open-source query optimizer. The role owns the design and evolution of the query optimizer core, directly shaping the performance and behavior of data processing for transactional, time-series, and analytical workloads. You will be responsible for the MongoDB Query Language and the full lifecycle of each query, from parsing through optimization and plan selection. The position requires deep collaboration across compiler, language transpiler, and distributed storage initiatives to evolve the optimizer end to end. You will work on high-impact problems that influence user experience across our global footprint and diverse deployment models.

Key facts

What you'll do

Investigate and analyze complex query execution patterns to identify optimization opportunities and systemic bottlenecks across diverse workload scenarios.

Design and prototype new optimization strategies that address flexible schema requirements while preserving correctness and performance in distributed environments.

Evaluate alternative execution models by tracing query behavior across large, heterogeneous code bases written in systems programming languages.

Partner with compiler and language teams to refine the translation layer between user intent and internal representations, improving robustness and efficiency.

Lead the definition of architectural direction for query optimization components, setting standards for scalability, maintainability, and extensibility.

Coordinate with client drivers, cloud services, enterprise tools, support, consulting, education, and marketing teams to align optimization changes with product and operational goals.

Implement and validate new diagnostic capabilities that expose optimizer decisions, enabling users and engineers to understand and reason about plan choices.

Guide code reviews and design documentation for optimizer-related features, ensuring rigorous engineering practices and consistency across a large, feature-rich codebase.

Mentor engineers across the organization, fostering a culture of deep database internals expertise and continuous learning in query systems research.

Contribute to the long-term technical roadmap of the query optimization group, translating research insights into actionable product milestones.

Requirements

Bring 10+ years of experience in data management systems, distributed systems, or large-scale backend engineering to the role.

Demonstrate a track record of building production-level code that serves a large user base with robust design structure and rigorous code quality.

Hold a degree in Computer Science or a similar field, or possess equivalent practical experience, with strong competencies in data structures, algorithms, and software design and architecture.

Showcase experience with large code bases written in C++ or another systems programming language, as you will need to trace down defects and estimate work complexity.

Possess a strong foundation in core database internals, where direct query optimization experience is a significant advantage though not mandatory.

Be prepared to engage with cutting-edge research in query systems to inform design decisions and challenge existing assumptions.

Apply deep knowledge of product strengths and weaknesses to provide technical vision and direction for optimizer initiatives.

Commit to setting initiative-level strategy, architecting plans, and leading the team toward successful execution in a fast-paced environment.

Nice to have

Preferred background in compilers, language transpilers, or distributed storage systems that intersect with query processing.

Experience contributing to open-source database projects or operating in environments with high-scale, low-latency data platforms.

Familiarity with modern analytical and time-series workloads, and the nuances of optimizing for flexible schema document models.

Practical notes

This role can be based out of our US offices or remotely in the North America region.

Work arrangements align with office-based and remote models, with schedules coordinated for convenient work hours across time zones.

No explicit travel, visa, or deadline constraints are specified in the source material.

About MongoDB

MongoDB is built for change, empowering customers and teams to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB's unified data platform, the most widely available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure.