Job Title: Senior MongoDB Performance Engineer

Location: Austin, TX / Sunnyvale, CA

Job Summary

We are seeking a highly experienced Senior MongoDB Performance Engineer with strong expertise in MongoDB performance tuning, query optimization, indexing, sharding, replication, and WiredTiger internals. The ideal candidate will be responsible for improving the performance, scalability, reliability, availability, and cost efficiency of large-scale MongoDB environments.

This is a hands-on database engineering role, focused primarily on MongoDB performance and operations rather than application development. The candidate should have extensive experience troubleshooting production MongoDB environments and optimizing clusters, queries, indexes, schemas, and infrastructure.

Key Responsibilities

• Perform advanced MongoDB performance tuning and optimization across production environments.
• Analyze slow queries and aggregation pipelines using Explain Plans, MongoDB Profiler, logs, and performance metrics.
• Design and optimize MongoDB indexing strategies, including compound, partial, wildcard, TTL, text, and geospatial indexes.
• Apply the Equality, Sort, Range (ESR) methodology to improve query performance.
• Identify and remove unused or redundant indexes to reduce write overhead and cache pressure.
• Tune WiredTiger storage engine parameters, including cache, eviction, checkpoints, journaling, compression, and filesystem cache.
• Analyze and optimize read/write workloads and read/write concern semantics.
• Operate and scale large MongoDB replica sets and sharded clusters.
• Design effective shard keys and sharding strategies based on workload, scalability, distribution, and query patterns.
• Manage MongoDB balancer operations, chunk distribution, hot chunks, jumbo chunks, zones, and resharding.
• Develop and maintain backup, restore, and Point-in-Time Recovery (PITR) strategies.
• Perform MongoDB upgrades, patching, and maintenance with minimal downtime.
• Monitor cluster health, throughput, latency, resource utilization, and capacity.
• Troubleshoot production performance issues and perform detailed root-cause analysis.
• Use Python scripting to automate MongoDB administration, monitoring, performance analysis, and operational activities.
• Partner with application and engineering teams on MongoDB data modeling and schema design.
• Review schema and index changes for performance and scalability impact.
• Provide database capacity planning, performance standards, operational runbooks, and best practices.
• Optimize underlying infrastructure, including AWS EC2 instances and EBS storage, IOPS, and throughput.
• Support MongoDB deployments on Kubernetes, including StatefulSets, storage classes, resource limits, anti-affinity, and storage configuration.

Required Technical Skills

• 8–10 years of relevant database engineering experience.
• Expert-level experience with MongoDB.
• Strong hands-on experience in MongoDB Performance Engineering.
• Expert knowledge of:
• MongoDB Aggregation Framework
• Query Optimization