Requirements

8+ years with PostgreSQL in production: schema design, query optimization, partitioning, replication, and performance tuning under write-heavy, high-throughput workloads
8+ years building Java Spring Boot services: REST APIs, JDBC, connection pooling, and JVM performance profiling
Experience with Kafka or equivalent streaming systems: consumer groups, offset management, and partition lag debugging
Track record operating distributed systems on AWS: microservices, multi-silo deployments, Terraform
Strong cross-system debugging skills: tracing a serving delay from a Datadog metric to a Humio log to a code path
Comfort with AI-assisted development and agentic engineering practices
A bias to ship and iterate alongside product and design partners
A genuine excitement for significantly scaling large data systems

Nice to have

Database migration experience (evaluating and cutting over between storage systems)
Flink, Spark, or lakehouse formats (Delta Lake, Iceberg, Parquet)
Kubernetes operations (StatefulSets, HelmReleases, stateful workloads)
Mentoring engineers and driving technical decisions through RFCs/ADRs
Interest in the cryptocurrency

Own and improve our data ingest Java service for enriched transfers generation and aggregations
Design and tune PostgreSQL transaction batching, indexing, and replication strategies
Contribute to the next-generation architecture, run PoCs, benchmark latency, and contribute to delivering the next generation to PROD
Build and maintain scalable API services on AWS that handle thousands of requests per second
Help automate network onboarding end-to-end
Debug production issues across microservices, define SLOs, and participate in the on-call rotation
Integrate LLM-based tools into daily engineering work and build agentic automation for operational tasks