Cloud Engineer - Senior (Observability - Datadog)

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.

"STRONG DATADOG EXPERIENCE NEEDED" 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-backend trace correlation to isolate bottlenecks in applications,

platforms, middleware, and downstream dependencies. - Partner with engineering

teams to define and implement remediation, tuning, and architectural

improvements based on telemetry evidence. - Define and implement trace-based

SLOs, deployment tracking, and change-correlation workflows so performance

regressions are detected and attributed to specific releases, versions, or

configuration changes. - Provide senior technical leadership during major

incidents, delivering impact analysis, contributing to root-cause analysis, and

owning post-incident observability gaps. Capacity, Reliability, and Continuous

Improvement - Analyze operational telemetry and trend data to identify capacity

risks, recurring constraints, and opportunities for efficiency. - Build and

maintain capacity and performance dashboards and reports that communicate

posture, risk, and recommendations to technical and leadership stakeholders. -

Define capacity thresholds, alert baselines, and trigger points for scaling,

technology refresh, and resource reallocation. - Drive continuous improvement of

observability coverage, alert quality, runbook linkage, and operational maturity

aligned to SEC SLA/KPI expectations. REQUIRED QUALIFICATIONS Citizenship/Work

Authorization: Must meet contract requirements. Clearance: Ability to obtain and

maintain SEC Public Trust (or higher if required). EXPERIENCE - Minimum 8 years

of experience in IT infrastructure or platform engineering roles, including 5+

years focused on observability, performance engineering, or site reliability

engineering. - Demonstrated experience engineering and operating an enterprise

observability platform (Datadog strongly preferred; equivalent experience with

Dynatrace, New Relic, Splunk Observability, or Grafana/Prometheus stacks

considered). - Proven experience building APM and distributed tracing coverage

for production multi-tier applications -- including language-specific tracer

deployment, custom instrumentation of business transactions, service/dependency

mapping, continuous profiling, and RUM-to-backend trace correlation -- across

cloud and containerized workloads. - Proven experience leading complex

production performance and reliability problem-solving from telemetry to

remediation. - Hands-on experience monitoring Kubernetes or OpenShift clusters

and containerized workloads in production. TECHNICAL SKILLS - Enterprise

observability platforms (Datadog or comparable): metrics, logs, traces, APM,

RUM, synthetic, NPM - Instrumentation with OpenTelemetry, Datadog agents/SDKs,

and language-specific APM tracers (Java, . NET, Python, Node.js, Go) including

custom spans, trace sampling strategies, W3C TraceContext propagation, and

continuous profiling - Microsoft Azure and AWS monitoring services and

integrations (Azure Monitor, Log Analytics, CloudWatch, AWS X-Ray) - Container

and Kubernetes/OpenShift observability, including cluster, workload, and service

mesh telemetry - Cloud database monitoring: AWS RDS/Aurora (including

Performance Insights), Azure SQL/PostgreSQL/MySQL (Query Performance Insight),

and NoSQL/cache (DynamoDB, Cosmos DB, ElastiCache/Redis); query-level

performance tuning, execution-plan analysis, and Datadog DBM or equivalent deep

database APM - Infrastructure-as-code for monitoring (Terraform, Bicep, ARM) and

CI/CD-driven monitor/dashboard deployment - APM and distributed tracing:

service/dependency maps, trace analytics, RUM-to-backend correlation,

exception/error tracking, deployment tracking, and trace-based SLOs - Unified

tagging strategy and cardinality governance across metrics/logs/traces

(environment, service, version, ownership, data classification, cost center),

including custom tag enrichment and tag-driven access/cost controls - Alert

engineering, SLO/SLI design, error budget management, and alert-noise reduction

- Performance engineering, capacity analysis, and telemetry-driven root-cause

analysis - Integration of observability with ITSM (ServiceNow) and

on-call/paging workflows PREFERRED QUALIFICATIONS - Experience supporting

federal agency IT environments under FISMA/FedRAMP/NIST-aligned security and

compliance requirements. - Datadog certification (Fundamentals and/or

Administrator) or comparable enterprise observability certification. - Hands-on

experience with Red Hat OpenShift Virtualization (CNV/KubeVirt) or other

KubeVirt-based container virtualization observability. - Experience with

eBPF-based observability tooling and service mesh telemetry (Istio, Linkerd). -

Experience implementing SLOs and error budgets at enterprise scale and

integrating them into operational governance. - Experience with cost-aware

observability practices, including telemetry volume optimization and retention

tuning. - Experience integrating observability outputs with executive reporting,

SLA/KLI dashboards, and capacity forecasting. - ITIL 4 Foundation - AWS

Certified Solutions Architect - Associate (or higher) - Microsoft Certified:

Azure Administrator Associate (or higher) - Red Hat Certified Specialist in

OpenShift Administration (or equivalent) - HashiCorp Terraform Associate WORK

ENVIRONMENT / OTHER Operational Support: Supports a 24x7x365 operating

environment; participates in a defined on-call rotation and may require surge

support based on operational needs. Location: Telework Travel: As required per

contract direction. EDUCATION & EXPERIENCE BS and 4 – 8 years of prior relevant

experience or Masters with 2 – 6 years of prior relevant experience. Preferred

degree in a relevant field (e.g., Information Technology, Computer Science,

Engineering). If you're looking for comfort, keep scrolling. At Leidos, we

outthink, outbuild, and outpace the status quo — because the mission demands it.

We're not hiring followers. We're recruiting the ones who disrupt, provoke, and

refuse to fail. Step 10 is ancient history. We're already at step 30 — and

moving faster than anyone else dares. Original Posting: May 19, 2026 For U.S.

Positions: While subject to change based on business needs, Leidos reasonably

anticipates that this job requisition will remain open for at least 3 days with

an anticipated close date of no earlier than 3 days after the original posting

date as listed above. Pay Range: Pay Range $87,100.00 - $157,450.00 The Leidos

pay range for this job level is a general guideline only and not a guarantee of

compensation or salary. Additional factors considered in extending an offer

include (but are not limited to) responsibilities of the job, education,

experience, knowledge, skills, and abilities, as well as internal equity,

alignment with market data, applicable bargaining agreement (if any), or other

law. Leidos Leidos is an industry and technology leader serving government and

commercial customers with smarter, more efficient digital and mission

innovations. Headquartered in Reston, Virginia, with 47,000 global employees,

Leidos reported annual revenues of approximately $17.2 billion for the fiscal

year ended January 2, 2026. For more information, visit www.Leidos.com. Pay and

Benefits

Pay and benefits are fundamental to any career decision. That's why we

craft compensation packages that reflect the importance of the work we do for

our customers. Employment benefits include competitive compensation, Health and

Wellness programs, Income Protection, Paid Leave and Retirement. More details

are available here. Securing Your Data Leidos will never ask you to provide

payment-related information at any part of the employment application process.

And Leidos will communicate with you only through emails that are sent from a

Leidos.com email address. If you receive an email purporting to be from Leidos

that asks for payment-related information or any other personal information,

please report the email to [email protected]. Commitment and Diversity All

qualified applicants will receive consideration for employment without regard to

sex, race, ethnicity, age, national origin, citizenship, religion, physical or

mental disability, medical condition, genetic information, pregnancy, family

structure, marital status, ancestry, domestic partner status, sexual

orientation, gender identity or expression, veteran or military status, or any

other basis prohibited by law. Leidos will also consider for employment

qualified applicants with criminal histories consistent with relevant laws.