The opportunity

• Own the reliability, availability, performance, capacity, backup/restore, disaster recovery, and security posture of shared data systems.
• Operate and improve platforms such as Kafka, Redis, Elasticsearch, MariaDB and other NoSQL databases with tight SLAs.
• Build and maintain high-touch abstractions and self-service workflows for provisioning, schema evolution, common operational changes, and routine maintenance.
• Use programming and AI-assisted workflows to automate repetitive work, improve diagnostics, raise documentation quality, and shorten time-to-resolution during incidents.
• Implement, deploy, operate, and improve satellite tools that improve our platform and increase our operational leverage.
• Partner closely with internal engineering teams on data access patterns, query optimization, schema design, operational readiness, and safe adoption of shared infrastructure.
• Improve observability, alerting, SLOs, runbooks, and operational reviews so that systems are easier to understand and incidents are less likely to happen.
• Participate in on-call rotations and incident response.

Skills you should HODL

• Strong hands-on experience operating production-grade stateful or distributed systems.
• Solid software engineering skills in a language such as Python, Rust, Go, or similar, with a clear track record of automating infrastructure or operations work.
• Experience deploying and operating tools and services in production.
• Practical Kubernetes experience, especially around stateful workloads, upgrades, storage, and failure modes.
• Strong Linux, networking, and systems troubleshooting fundamentals.
• Experience with observability, alerting, incident response, and post-incident improvement.

Nice to haves

• MariaDB / PostgreSQL
• Kafka
• Redis / Valkey
• Elasticsearch / OpenSearch
• MongoDB, ClickHouse, Cassandra, or similar NoSQL / distributed data systems
• Terraform, GitOps, CI/CD, operators, or other automation-heavy infrastructure patterns
• Query tuning, schema design, replication, clustering, or high-availability design
• Data engineering or pipeline-adjacent technologies such as CDC, Kafka Connect, Flink, or similar