Senior Software Engineer, Capacity & Efficiency

Robinhood•Bellevue, WA

10d•Onsite

About The Position

The Capacity & Efficiency Engineering team builds software to manage, govern, and reduce Robinhood’s AWS cloud spend across compute, databases, and storage. The team works across cloud infrastructure, data engineering, and FinOps, managing the full lifecycle of cloud cost—from attribution and forecasting to fleet-scale infrastructure rightsizing—while maintaining reliability and cost effectiveness for a bursty, latency-sensitive trading platform. The Senior Software Engineer will own capacity and efficiency for Robinhood’s storage and database fleet, including Aurora clusters, S3, caches, and volumes. This is a 0-to-1 role building systems that size fleet resources to demand, including forecast-driven Aurora scaling, database and storage rightsizing, and S3 storage-class and lifecycle management. The role takes recommendations validated by the Storage team through to production automation that safely applies changes, with measurable impact on reliability during market peaks and AWS costs. The role is based in Robinhood’s Bellevue, Washington office, with in-person attendance expected at least three days per week.

Requirements

Deep hands-on experience operating AWS storage and databases at scale, especially Aurora or RDS (MySQL or PostgreSQL) and S3, including replication, read scaling, storage classes, and lifecycle management.
Capacity planning and forecasting experience, including modeling time-series demand, load testing, and translating traffic into instance counts, sizes, and storage growth.
A track record of rightsizing infrastructure from utilization data such as CPU, memory, IOPS, throughput, and bytes stored without harming latency or availability.
Strong Python or Go engineering skills.
Experience building automation that safely modifies production infrastructure, with guardrails, progressive rollout, and rollback built in.

Nice To Haves

Familiarity with AWS storage and database pricing, including S3 storage classes and requests, Aurora I/O-Optimized versus Standard, and Reserved Instances.
Experience with bursty, event-driven workloads such as trading, payments, or ticketing.
Experience with Spark, Airflow, or Kubernetes.

Responsibilities

Build forecast-driven capacity planning for the storage and database fleet using traffic history, load tests, and known events to scale resources up ahead of demand and back down afterward, with an expiry on every temporary capacity hold.
Design and build an Aurora capacity planner that sets reader counts and writer instance sizes based on demand and load signals, replacing fixed scaling schedules.
Rightsize databases, caches, and block storage, including RDS, ElastiCache, DynamoDB, and EBS, based on instance size, provisioned IOPS and throughput, and idle capacity; keep resources right-sized as load changes.
Manage S3 efficiency at scale, including storage-class and Intelligent-Tiering strategies, lifecycle and retention policies, noncurrent versions, incomplete uploads, and request costs, using Storage Lens and inventory data.
Turn recommendations into closed-loop automation with guardrails, progressive rollout, and rollback, in partnership with the Storage infrastructure team.
Handle constraints such as AWS capacity shortages, fallback instance types, and connection pooling.
Measure cost and reliability outcomes, including savings against baseline, forecast error, utilization, and capacity left behind after events.
Share forecasts with the pod rightsizing system so compute and storage can scale together.