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Big Data • Analytics
Supports delivery and implementation of enterprise IT solutions across infrastructure, platforms, and applications. Collaborates with engineering and architecture teams to validate requirements, support solution integration, monitor technical dependencies, resolve delivery risks, and ensure performance, reliability, security, and architectural alignment. The role also identifies opportunities for system optimization, automation, and improved operational efficiency while translating technical concepts for stakeholders.
Big Data • Analytics
Implements enterprise monitoring use cases under senior guidance, supports data onboarding, configures and tunes dashboards, alerts, and monitoring rules, and assists with incident workflow alignment. The role participates in troubleshooting, operational support, monitoring coverage validation, documentation, and issue escalation through ITSM channels.
Big Data • Analytics
Lead enterprise observability and monitoring integration, event-to-incident workflows, and monitoring-platform support. Build dashboards, operational views, and reports for technical and non-technical stakeholders. Support OpenTelemetry instrumentation, collector operations, and telemetry handling, while implementing automation with Splunk SOAR and Ansible. The role requires architecture and integration experience across monitoring, observability, or application performance management environments.
Big Data • Analytics
Lead technical strategy, architecture, and solution design for enterprise monitoring and observability platforms. Define telemetry ingestion, alerting, dashboarding, and ServiceNow/CMDB integrations; create architecture standards and artifacts; guide cross-functional teams and partners through complex implementations; assess customer infrastructure; brief senior stakeholders; support proposals and bids; and recommend solutions aligned with federal customer goals.
Big Data • Analytics
Configure, deploy, tune, and sustain enterprise monitoring platforms in secured environments. Develop dashboards, alerts, automation, and event-management workflows using Splunk SOAR and Ansible. Support integration testing and production rollouts, troubleshoot platform issues, collaborate on scalable monitoring solutions, and document configurations and procedures.
Big Data • Analytics
Design and maintain enterprise security architecture for ICAM applications; integrate security controls across applications, cloud, infrastructure, and DevSecOps; support security assessments, ATO documentation, vulnerability remediation and POA&M management; work with development teams to enforce SDLC security and resolve high-severity findings.
Big Data • Analytics
Tier 2 Application Systems Administrator providing advanced Help Desk support: administer user accounts and access (AIMS/PAS), manage MFA soft/hard tokens, triage incidents, coordinate service restoration, monitor SLAs and reporting, troubleshoot applications and system issues, document ticketing activities, and support English/Spanish operations.
Big Data • Analytics
Lead and perform QA across the SDLC for ICAM applications. Develop and run automated and manual tests, integrate testing into CI/CD, validate functionality, performance, security, and Section 508 accessibility, maintain test evidence and gates, support UAT and production incident validation.
Big Data • Analytics
Support ICAM system enhancements by gathering and documenting requirements, writing Agile user stories and acceptance criteria, coordinating with product owners and engineering, supporting UAT and Tier 1 customer support, maintaining SOPs and knowledge base content, and tracking risks, issues, and change requests.
Big Data • Analytics
Develop, integrate, test, deploy, and support ICAM applications using Java/Spring/Hibernate/Angular/MySQL. Commit code, maintain unit and automated tests, support CI/CD and zero-downtime deployments, troubleshoot Tier 2/3 incidents, perform root-cause analysis, write technical documentation, and participate in Agile ceremonies.
Big Data • Analytics
Lead development and deployment of machine learning models, provide technical leadership on AI/ML solutions, integrate models with data pipelines, build RPA automations, support data governance, evaluate analytics products, and present findings through dashboards and reports to stakeholders.



