Cloud Engineer - Senior (Observability - Datadog)
LeidosAbout the role
The Cloud Engineer - Senior (Observability - Datadog) supports the SEC ISS contract by engineering, operating, and continuously improving the enterprise observability platform across hybrid cloud and containerized environments. This role is hands-on: instruments services with distributed tracing, code-level profiling, and custom metrics; builds and tunes Datadog (or comparable) dashboards, alerts, APM, log pipelines, RUM, and synthetic monitors; then uses that telemetry to solve production performance, reliability, and capacity problems. The engineer partners with cloud, platform, and application teams to embed observability into Azure, AWS, and container platforms (OpenShift/Kubernetes), and drives reduction of alert noise, mean time to detect (MTTD), and mean time to resolve (MTTR). This position provides senior technical leadership for APM/distributed tracing strategy, SLO/SLI engineering, and data-driven operational decision-making in a 24x7x365 operating environment.
PRIMARY RESPONSIBILITIES
Observability Platform Engineering
- Engineer and operate the enterprise observability stack (Datadog or comparable), including metrics, logs, traces, APM, RUM, synthetic monitoring, and network performance monitoring.
- Build, tune, and maintain dashboards, monitors, SLOs/SLIs, and alerting policies that produce actionable signal and minimize noise.
- Instrument services, infrastructure, and containerized workloads using agents, OpenTelemetry, and language-specific APM tracers (Java, .NET, Python, Node.js, Go) with consistent span tagging, W3C TraceContext propagation, and unified service tagging across the estate.
- Develop and maintain integrations between observability platforms, ITSM (ServiceNow), CI/CD pipelines, and on-call/paging workflows.
- Define and enforce a unified tagging standard (environment, service, version, team/ownership, data classification, cost center) across metrics, logs, and traces; manage tag cardinality, governance, and custom business tags to keep telemetry queryable, attributable, and cost-controlled.
Cloud and Container Monitoring Engineering
- Design and deliver monitoring coverage for Microsoft Azure and AWS workloads, including PaaS services, serverless, networking, identity, managed databases, and cloud-native data services.
- Engineer managed database observability across AWS RDS/Aurora (MySQL, PostgreSQL, SQL Server, Oracle), Azure SQL/PostgreSQL/MySQL, and NoSQL/cache services (DynamoDB, Cosmos DB, ElastiCache/Redis), including query-level performance analytics, slow-query and execution-plan capture, lock/deadlock/wait analysis, connection pool and session monitoring, replication lag, storage/IOPS saturation, and backup/HA health -- correlating database spans with upstream APM traces.
- Engineer container-platform observability for OpenShift/Kubernetes, covering cluster health, control plane, nodes, pods, namespaces, ingress, service mesh, and workload APM.
- Build standardized, reusable monitoring modules deployable via infrastructure-as-code (Terraform, Bicep, ARM) and CI/CD.
- Support hybrid visibility across on-premises, cloud, and containerized workloads with correlated telemetry.
Performance Engineering and Problem Solving
- Lead data-driven investigation and resolution of complex performance, latency, saturation, and reliability issues across the estate.
- Use APM distributed traces, service/dependency maps, continuous code profiling (CPU, memory, lock contention), database query analytics, exception/error tracking, and RUM-to-backen
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