About the position
MongoDB's mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure. Atlas allows customers to build anywhere—on the edge, on premises, or across cloud providers. With offices worldwide and over 175,000 developers joining MongoDB every month, it's no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications. Atlas Data Federation gives developers a powerful way to query, transform, and analyze data combined across a variety of sources—including multiple MongoDB Atlas clusters and cloud object storage (like Amazon S3)—without needing to copy or move the data. By extending the MongoDB Query Language (MQL) to remote sources, we offer a seamless way to work with distributed data through a single interface. Our team builds and operates the backend systems that make this possible—from query planning and optimization, to execution and data access across heterogeneous backends. We own critical infrastructure that operates at high volume and low latency, handling complex federated queries over exabytes of data.
Responsibilities
- Design and implement core components of the distributed query engine.
- Improve the performance, memory efficiency, and reliability of systems.
- Enhance the distributed control plane for infrastructure and workload routing.
- Participate in on-call rotations, leading incident response and postmortem analysis.
- Collaborate with other MongoDB teams to ensure seamless integration and a cohesive developer experience.
Requirements
- 3+ years of experience working on database or storage internals, or building core components of data processing systems such as query execution engines, storage layers, workload optimization, or autonomous tuning.
- Proficiency in systems programming with languages like Go, Java, C++, or Rust.
- Hands-on experience building and operating distributed systems at scale.
- Excellent verbal and written technical communication skills.
- Desire to collaborate with colleagues, mentor fellow engineers, and lead projects.
- Bachelor's or Master's degree in Computer Science or a related field, or equivalent practical experience.
Benefits
- Equity participation in the employee stock purchase program.
- Flexible paid time off.
- 20 weeks fully-paid gender-neutral parental leave.
- Fertility and adoption assistance.
- 401(k) plan.
- Mental health counseling.
- Access to transgender-inclusive health insurance coverage.
- Health benefits offerings.
