Sr Software Architect - Global Network Services

The Role: We are looking for a Data Engineer to design, build, and own the observability pipeline that serves as the central nervous system for our entire platform. Your mission is to engineer the systems that collect, process, and correlate massive streams of telemetrylogs, metrics, and tracesfrom our globally distributed infrastructure. You will transform raw, disparate data points into a unified, coherent, and actionable view of our network's health and performance, empowering our engineering teams to detect, diagnose, and resolve issues with speed and precision. Responsibilities: Build and Manage Data Ingestion Pipelines: Architect and implement robust, scalable data ingestion pipelines using tools like Fluentd or Logstash to collect telemetry from thousands of sources across our multi-cloud environment. Own Observability Datastores: Deploy and manage the specialized databases that power our observability stack, including time-series databases (e.g., Prometheus, InfluxDB) for metrics and search indexes (e.g., Elasticsearch) for logs. Develop Data Correlation Engines: Design and build systems that process and correlate disparate data streams in real-time. Your work will enable engineers to connect a specific log error to a metric spike or a distributed trace, providing a holistic view of system behavior. Ensure Data Quality and Reliability: Implement data validation, quality checks, and monitoring to ensure the accuracy, consistency, and timeliness of the data flowing through the observability pipeline. Collaborate and Enable: Work closely with our control plane, data plane, and infrastructure teams to understand their monitoring needs and provide them with the data, dashboards, and tools required to maintain operational excellence. Required Qualifications: 3+ years of experience in data engineering, site reliability engineering (SRE), or a similar role with a focus on observability. Hands-on experience building and managing data pipelines with ingestion tools such as Fluentd, Logstash, Fluent Bit, or Vector. Strong experience with time-series databases like Prometheus or InfluxDB. Proficiency with search and analytics engines, particularly Elasticsearch, and the ELK Stack (Elasticsearch, Logstash, Kibana). Solid programming and scripting skills in a language like Python or Go. A strong understanding of the three pillars of observability: metrics, logs, and traces. Preferred Qualifications: Experience building and operating systems in a multi-cloud environment (AWS, Azure, GCP). Familiarity with containerization and orchestration technologies (Docker, Kubernetes). Experience with distributed tracing and telemetry standards like OpenTelemetry. A conceptual understanding of networking principles. Experience working in a fast-paced startup environment.