About this role

Lead end-to-end MongoDB performance optimization including query tuning, execution plan analysis, and index design
Design and implement scalable data models optimized for high read/write throughput and low latency
Architect and operate large-scale sharded clusters using range-based and hash-based strategies
Optimize shard key selection, chunk distribution, and balancing to prevent hotspots and improve performance
Manage cross-shard query efficiency and reduce scatter-gather impact across distributed workloads
Support large production environments (hundreds of nodes, multi-region deployments) with a focus on availability and resilience
Implement and maintain high availability, disaster recovery, and failover strategies across regions
Automate database operations, monitoring, and maintenance tasks using Python or shell scripting
Partner with application teams on data modeling, query design, and performance best practices
Participate in 24x7 on call Support

6+ years of experience as a MongoDB Engineer or DBA in large-scale production environments
6+ years of experience in MongoDB sharding, replication internals, and distributed architecture design
2+ years of experience with Python, Powershell, RedHat Linux, Mac OS, IIS, and Active Directory
2+ years with cloud technologies such as Google Cloud and Azure
Bachelor’s degree in computer science, or a relevant field, or an equivalent combination of education, work, or military experience

Senior MongoDB Database Engineer

Key skills