MongoDB Performance Engineer

VOLTO Consulting; Austin (TX); On-site; USD 130,000 - 180,000; Full time

Job summary

VOLTO Consulting is seeking a Sr MongoDB Performance Engineer in Austin to own throughput, latency and reliability of MongoDB deployments. This hands-on role requires deep expertise in MongoDB internals, query optimization, and sharding strategies to scale global workloads.

You will profile slow queries, design indexes, tune WiredTiger, manage backups, and collaborate with ops and dev teams to maintain cost-efficient, high-availability clusters in a cloud environment.

Qualifications

• Must have expert level MongoDB knowledge and hands-on experience.
• Strong performance tuning abilities and low-latency focus.
• Fluency with aggregation, indexing, and read/write semantics.
• Experience with explain plans, profiling, and query optimization.
• Deep understanding of WiredTiger internals and cache behavior.
• Experience with replication and sharding at scale, shard-key design.
• Scripting for automation in Python is required.

Responsibilities

• Profile and optimize slow queries and pipelines using explain plans and profiler data.
• Design and rationalize indexes to reduce write cost and cache pressure.
• Tune WiredTiger, manage cache, eviction, compression, and journaling.
• Operate and scale sharded clusters; manage balancer and resharding as needed.
• Own backup/restore, PITR, and rolling upgrades with minimal downtime.
• Collaborate with application teams on data modeling and schema changes.

Skills

MongoDB expertise

Performance tuning

Aggregation framework

read/write/read-concern semantics

Explain-plan & profiler

WiredTiger internals

Replication & sharding at scale

Python scripting

Cluster/query/index/schema tuning

Sharding strategy & shard keys

Monitoring sharded clusters

Tools

Kubernetes operator experience for stateful MongoDB

Terraform/Ansible (Infrastructure-as-Code)

Job description

Job Title: Sr MongoDB Performance Engineer

Role Descriptions

Must Have Skills:

• Expert in MongoDB
• Strong experience in Performance tuning
• Fluent in the aggregation framework, indexing strategy, and read/write/read-concern semantics.
• Strong explain-plan and profiler-driven query optimization
• WiredTiger internals: cache, eviction, checkpoints, journal, compression, document-level concurrency.
• Replication and sharding operations at scale, including shard-key design trade-offs.
• Scripting for automation Python
• Strong experience with tuning of specific clusters, queries, indexes and schemas
• Good experience designing sharding strategy and shard keys; plans resharding and zone strategy
• Strong experience operating and monitoring existing sharded clusters; runs balancer, fixes hot chunks

Nice To Have Skills

• MongoDB certification
• Kubernetes operator experience for stateful MongoDB; Infrastructure-as-Code (Terraform/Ansible).

Technical/Functional Skills

MongoDB Performance Engineer to own the throughput, latency, scalability and operational reliability of MongoDB landscape. This is a hands‑on database engineering role not an application‑developer role.

The engineer is accountable for making MongoDB fast, predictable and cost‑efficient at scale.

Performance engineering (Primary)

Profile and optimize slow queries and aggregation pipelines using explain plans, the database profiler, and log analysis.

Design, review and rationalize indexes (compound, partial, wildcard, Time To Live (TTL), text, geospatial) applying the Equality, Sort, Range (ESR) rule; eliminate unused and redundant indexes that inflate write cost and cache pressure.

Tune the WiredTiger storage engine: internal cache sizing, eviction and checkpoint behavior, compression, and journaling, balanced against filesystem cache.

Operations & reliability

Operate and scale sharded clusters: balancer management, chunk/range distribution, jumbo‑chunk remediation, and (on modern versions) resharding.

Own backup/restore and Point‑In‑Time Recovery (PITR) strategy, plus rolling upgrades and patching with zero or minimal downtime.

Infrastructure, OS & platform

Right‑size EC2 instances and EBS volumes (Input/Output Operations Per Second (IOPS) and throughput provisioning); on Kubernetes, own StatefulSet storage class, resource requests/limits, anti‑affinity, and cache sizing against container memory limits.

Partner with application teams on data modeling; review schema changes; publish standards, runbooks and capacity guidance.

Skills: Digital : Mongo DB~Performance Engineering