Staff Engineer, MongoDB

• 10+ years experience in software engineering, with a focus on backend and distributed storage systems
• Expertise in large-scale storage systems, such as distributed databases, cloud object storage (S3, Azure Blob, GCS), or data lake technologies (Iceberg, Delta Lake, Hudi, etc.)
• Strong background in designing and optimizing storage layers, indexing, and data lifecycle management
• Experience optimizing query engines for high-volume, low-latency federated data access
• Track record of improving system reliability, observability, and cost-efficiency
• Experience with Kubernetes-based deployment of distributed storage or query systems
• Proficiency in Go or Java (preferred, but not required)
• Deep understanding of query optimizers, storage formats (Parquet, ORC), and indexing strategies
• Experience with disaggregated storage and cloud-native data lake solutions
• Proven ability to lead technical initiatives as an individual contributor while mentoring senior engineers and driving technical excellence within a team

• MongoDB Atlas Data Federation enables customers to query, transform, and analyze data across multiple sources (MongoDB clusters, cloud object storage, and external databases) through a unified MongoDB query interface—without moving or copying the underlying data. Our system processes hundreds of millions of queries per month and handles exabytes of customer data at scale
• MongoDB Atlas Online Archive provides low-cost, tiered storage for managing infrequently-accessed, read-only data. By optimizing storage layouts during ingestion and rebalancing data dynamically, Online Archive ensures efficient query performance and scalability while managing petabytes of customer data in a rapidly growing system
• As a Staff Engineer on the Atlas Data Federation and Archiving team, you will lead the design, optimization, and scalability of our storage and federated query systems. This role focuses on high-performance distributed storage, data lifecycle management, and efficient data retrieval at scale
• You will work on storage optimization, query execution, and cost-effective data retention strategies—ensuring reliability, performance, and efficiency for thousands of MongoDB Atlas customers who depend on our solutions for critical business operations
• This is a high-impact role for engineers passionate about large-scale data storage, distributed query processing, and system resilience
• Architect and optimize large-scale storage solutions for federated data access, ensuring efficient retrieval, indexing, and query performance
• Optimize data archival pipelines for high-throughput ingestion, durability, and cost-efficiency
• Improve data tiering and lifecycle policies for moving and querying data efficiently across hot, warm, and cold storage tiers
• Reduce operational costs through intelligent storage layout, compaction strategies, and query execution optimizations
• Improve and scale our distributed query execution engine, optimizing it for multi-source federated queries and data lake processing
• Enhance query performance across object storage (e.g., S3, GCS, Azure Blob) by optimizing indexing, partitioning, and compaction techniques
• Implement workload-aware autoscaling for query execution and data processing
• Reduce incident rates by improving system resilience, failover mechanisms, and observability
• Guide architectural decisions and lead design reviews across engineering teams
• Mentor engineers in distributed systems, data storage optimization, and operational excellence
• Partner with Product Management to define the technical roadmap for storage and data federation solutions
• Participate in on-call rotation, providing senior oversight for incident response and postmortem retrospectives

• Rich health insurance coverage
• Virtual & on-site fitness classes
• Health screenings & telemedicine
• Access to transgender-inclusive health insurance coverage
• Global and internal mobility opportunities
• Equity & Employee Stock Purchase Program
• Pension & retirement programs
• Income Protection
• Flexible PTO is offered to every US employee & competitive time off policies for non-US employees
• Employee Assistance Program
• Mental health counseling
• Free meditation app access
• Fertility & adoption financial assistance
• Parental counseling for new parents
• 20 weeks of fully paid gender neutral parental leave & flexible work arrangements
• 4 weeks of emergency care leave

Total funding: $311.1m

MongoDB is an open-source, cross-platform, document-oriented database system. It stores data as JSON-like documents and is written in C++, Go, JavaScript and Python.