Sr Software Engineer, Storage

Responsibilities

• Design and build autoscaling systems for storage clusters — automated provisioning, scale-up/scale-down policies, cluster rebalancing, and node lifecycle management.
• Own the infrastructure-as-code stack (Terraform) that defines and deploys storage infrastructure end-to-end on AWS.
• Build self-healing automation: health checks, automated failover, capacity rebalancing, and remediation controllers that resolve issues before they page anyone.
• Develop the CI/CD pipelines and deployment tooling for storage services — safe rollouts, canary deployments, automated rollback.
• Design and implement observability for the entire storage platform — metrics, dashboards, SLOs, alerting, and capacity forecasting that drive automated scaling decisions.
• Own cluster management tooling: provisioning new tenants, managing cluster topology, coordinating upgrades and migrations with zero downtime.
• Drive performance and cost optimization across the storage data path: ingest pipelines, compaction, partitioning, and query execution.
• Partner with product engineering to define scalability limits, load test new features, and harden the system for production readiness.
• Contribute to incident response and lead blameless post-mortems, turning operational surprises into systemic automation.

Requirements

• Significant experience building platform/infrastructure systems that manage, scale, and operate distributed services autonomously.
• Strong software engineering skills in TypeScript/Node.js, Go, or similar languages.
• Deep hands-on experience with infrastructure-as-code (Terraform) and AWS services (EC2, ECS/EKS, ASGs, DynamoDB, S3, CloudWatch).
• Experience designing and implementing autoscaling systems, cluster orchestration, or automated provisioning for stateful workloads.
• Track record operating data-intensive systems at scale — OLAP databases, NoSQL stores, or distributed storage platforms.
• Strong platform engineering fundamentals: SLOs, error budgets, capacity planning, incident response, and a bias toward eliminating toil through software.
• Comfortable working with high autonomy in a remote, distributed team.
• Strong understanding of Linux systems, networking, and performance profiling at the infrastructure level.

Nice-to-Haves

• Experience with DynamoDB or similar NoSQL databases at high throughput — partition design, capacity management, GSI optimization.
• Background in cluster management for OLAP or analytical databases — automated provisioning, rolling upgrades, replication topology.
• Experience with object storage and data lake architectures (S3, Parquet/ORC formats).
• Knowledge of data pipeline optimization: batching strategies, write amplification reduction, partition pruning, compaction policies.
• Background in capacity planning, cost optimization, and resource forecasting for storage-heavy workloads on AWS.
• Experience building internal platforms or developer tooling that other engineers consume.
• Opinions about what makes a great on-call experience and a track record of making on-call better for everyone.

This position will require stand-by, on-call, or off-hours duties.