Senior Database Platform Engineer

Kraken is a mission-focused company rooted in crypto values, seeking to accelerate the global adoption of crypto. The Senior Database Platform Engineer will own the reliability, availability, and performance of shared data systems while improving operational processes and collaborating with internal engineering teams.

Responsibilities:

• 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

Requirements:

• 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
• 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