Software Developer 5

Oracle Oracle · Enterprise · Seattle, WA +1

Software Developer 5 role at Oracle focused on building and operating cloud-scale observability platforms, specifically logging services. The role involves designing, developing, and optimizing distributed systems for high-throughput log ingestion, processing, storage, indexing, search, and query at massive scale, serving both internal OCI services and external customers. Key responsibilities include technical leadership, architectural decisions, performance bottleneck resolution, and mentoring engineers, with a focus on reliability, cost-efficiency, and operational excellence in a hyperscale cloud environment.

What you'd actually do

  1. Lead the design, development, and operation of cloud-scale logging platforms supporting log collection, ingestion, processing, storage, indexing, search, and query.
  2. Architect and implement highly scalable, resilient, and cost-efficient logging systems that serve internal OCI services and external customers.
  3. Design and optimize distributed systems capable of ingesting, storing, and querying massive volumes of log data with stringent latency, availability, durability, and compliance requirements.
  4. Develop scalable storage, indexing, and retrieval solutions for high-volume logs and large-scale log analytics workloads.
  5. Build and enhance query, search, and retrieval services that provide fast, reliable, and intuitive access to log data.

Skills

Required

  • Java
  • Go
  • C
  • C++
  • Python
  • Cloud scale products and services
  • Mutli-tenant services
  • Concurrent Programming
  • Open source technologies for development and management
  • Cloud technologies
  • Full product/service development and operations lifecycle
  • Strong communication and analytical skills
  • Able to adapt to fast changing requirements

Nice to have

  • Observability Solutions (metrics, logs, traces)
  • Kafka
  • Lucene
  • Spark
  • Parquet
  • Kubernetes
  • Terraform
  • Performance, Scalability, Reliability and Recovery of large scale distributed systems

What the JD emphasized

  • cloud-scale logging platforms
  • massive volumes of log data
  • high-volume logs
  • large-scale log analytics workloads
  • logging storage and query architectures