Robert Yang

I’m a senior software engineer with 6+ years building large-scale backend systems for observability and financial platforms. I combine hands-on delivery with technical leadership, bringing deep expertise in Java and distributed systems, plus event-driven data pipelines and observability tooling. I also apply blockchain concepts—like smart contracts and stablecoin token flows—within monitoring and analytics contexts.

At Datadog, I work on the cloud observability and monitoring platform used by tens of thousands of engineering teams. I’ve built backend features for end-to-end distributed tracing with Spring Boot and gRPC, and I’ve developed high-volume ingestion pipelines using Apache Kafka and Apache Flink for metrics, logs, and traces at petabyte scale. I also improved log management workflows across Kibana and Grafana, and I contributed alert/monitor configuration services in PostgreSQL and Redis to reduce mean time to detection.

I’ve extended Datadog products with AI-assisted anomaly detection and vector search capabilities to surface unusual patterns and monitor LLM application performance. I built and maintained integration coverage for telemetry ingestion using Node.js and Spring Boot, and I instrumented services with structured logging, distributed tracing, and metric collection via OpenTelemetry. I collaborate cross-functionally with product, design, and platform teams, support SRE practices through on-call and incident response, and mentor engineers through code reviews and technical design sessions.

Previously, at Bloomberg LP, I helped build systems powering the Bloomberg Terminal used by 350,000+ financial professionals. I worked on low-latency market data processing, data entitlements and access control with OAuth 2.0 and role-based authorization, and real-time communications using WebSockets and real-time APIs. I’ve supported compliance-aligned data handling (including GDPR), engineered feed resilience using idempotency and event-driven approaches, operated on-call for data feed disruptions, and helped reduce pipeline processing latency by ~12–13% while owning major feature delivery adopted by thousands of active users.