Senior Dynatrace Engineer at MNC Client · Remote only · 5 - 9 years · Remote only · Posted 10 Sep 2026

Key Responsibilities
- Design, deploy, configure, upgrade, and administer enterprise-scale Dynatrace environments.
- Deploy and manage OneAgent, ActiveGate, extensions, and monitoring configurations across application and infrastructure environments.
- Implement observability for applications, APIs, microservices, databases, containers, Kubernetes, cloud platforms, and traditional infrastructure.
- Configure service detection, process groups, management zones, tags, naming rules, metrics, logs, traces, and topology.
- Develop operational and executive dashboards, notebooks, reports, SLOs, and alerting strategies.
- Configure and optimize Davis AI problem detection, anomaly detection, baselines, and root-cause analysis.
- Implement Real User Monitoring (RUM), Synthetic Monitoring, Session Replay, distributed tracing, and log monitoring as required.
- Analyze application performance issues, service dependencies, transaction traces, response times, resource utilization, and infrastructure bottlenecks.
- Lead troubleshooting of complex production performance and availability incidents using Dynatrace telemetry.
- Reduce alert noise through effective event correlation, thresholds, anomaly-detection configuration, and monitoring standards.
- Integrate Dynatrace with enterprise platforms such as ServiceNow, Jira, PagerDuty, Splunk, CI/CD pipelines, and collaboration/notification tools.
- Automate Dynatrace configuration and deployment using APIs, configuration-as-code, scripting, and DevOps tooling.
- Work closely with application, infrastructure, cloud, SRE, DevOps, production support, and operations teams to define observability requirements.
- Establish Dynatrace monitoring standards, reusable configurations, governance, and best practices.
- Perform platform health checks, capacity assessments, license/usage optimization, and monitoring coverage reviews.
- Create technical documentation, runbooks, architecture diagrams, troubleshooting guides, and operational procedures.
- Mentor junior engineers and provide technical leadership for observability initiatives.
Required Technical Skills
- 5–8+ years of overall IT experience with significant experience in application/infrastructure monitoring or observability.
- 3–5+ years of hands-on Dynatrace experience in enterprise environments.
- Strong knowledge of:
- Dynatrace OneAgent and ActiveGate
- Application Performance Monitoring (APM)
- Infrastructure Monitoring
- Distributed Tracing
- Real User Monitoring (RUM)
- Synthetic Monitoring
- Log Monitoring and Analytics
- Metrics, traces, logs, and events
- Davis AI and automated root-cause analysis
- Dashboards, SLOs, alerting, and anomaly detection
- Dynatrace APIs and automation
- Experience monitoring Java/JVM, .NET, web applications, APIs, microservices, and databases.
- Experience with Kubernetes, Docker, OpenShift, or other container platforms.
- Working knowledge of at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform.
- Strong understanding of application architecture, HTTP/HTTPS, REST APIs, networking, operating systems, and middleware.
- Experience with Linux and Windows environments.
- Scripting/automation experience using Python, PowerShell, Bash, Ansible, Terraform, or similar technologies.
- Experience integrating monitoring platforms with ITSM, incident management, and DevOps tools.
- Strong analytical and production troubleshooting skills.
Preferred Skills
- Experience with Dynatrace Grail, DQL (Dynatrace Query Language), OpenPipeline, and the latest Dynatrace platform capabilities.
- Knowledge of OpenTelemetry (OTel) and modern telemetry standards.
- Experience implementing observability for large-scale Kubernetes and cloud-native environments.
- Familiarity with SRE practices, including SLIs, SLOs, error budgets, and observability-driven incident management.
- Knowledge of additional monitoring platforms such as Splunk, AppDynamics, Datadog, New Relic, Grafana, Prometheus, or ELK.
- Experience with infrastructure-as-code and configuration-as-code approaches.
- Dynatrace certifications are preferred.
Professional Skills
- Strong problem-solving and root-cause analysis capabilities.
- Ability to troubleshoot complex application and infrastructure performance issues independently.
- Strong written and verbal communication skills.
- Ability to work effectively with application owners, developers, SREs, infrastructure teams, and senior stakeholders.
- Ability to translate business and operational requirements into observability solutions.
- Experience working in enterprise production environments with incident, problem, and change-management processes.
- Ability to mentor engineers and drive technical standards across teams.
Education & Certification
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent professional experience.
- Dynatrace Associate/Professional-level certification is desirable.
- Cloud, Kubernetes, ITIL, SRE, or DevOps certifications are advantageous.
Experience Level
Senior Engineer
- Overall Experience: 5–8+ years
- Dynatrace/Observability Experience: 3–5+ years
- Expected proficiency: Advanced hands-on implementation, administration, troubleshooting, automation, and solution design

Similar jobs (10)
Job Summary
A Senior Full Stack Observability Engineer – AI Ops & Autonomous Observability to handle / manage , Design and implement enterprise-wide observability across applications, infrastructure, cloud, network, database and digital services. Lead adoption of Datadog, AI Ops, SRE and Autonomous Observability. Build agentic AI and multi-agent orchestration solutions that automate operational workflows and enable autonomous operations.
Technical Skills
- Datadog (Expert)
- OpenTelemetry
- Distributed Tracing
- Application Performance Monitoring
- AI Ops
- LangGraph/CrewAI/AutoGen/Semantic Kernel
- Python
- Azure, AWS
- Kubernetes
- ServiceNow Integration
Enterprise Observability Strategy
- Define observability standards, governance and operating model.
- Create monitoring roadmaps, service health frameworks, business service dashboards and dependency mapping.
Full Stack Observability Scope
- Applications, APIs, microservices and user journeys.
- Windows, Linux, VMware, storage and infrastructure platforms.
- Azure and AWS.
- Network monitoring, SQL and NoSQL databases.
Datadog Platform
- Deploy and optimize Datadog solutions.
- Build dashboards, monitors, alerts and observability-as-code frameworks.
- Integrate Datadog with ServiceNow, Teams and enterprise tooling.
- New Relic exposure is optional.
AI Ops Responsibilities
- Event correlation and noise reduction.
- Predictive analytics and anomaly detection.
- Incident intelligence and root cause analytics.
- Proactive issue identification and MTTR reduction
Job Description
We are looking for an Azure Cloud & Observability Engineer with strong experience in Azure infrastructure and enterprise monitoring tools such as Splunk, Grafana, and AppDynamics.
Responsibilities
- Design, deploy, and manage Azure cloud infrastructure and services.
- Monitor application and infrastructure performance using Splunk, Grafana, and AppDynamics.
- Configure dashboards, alerts, health rules, and monitoring metrics.
- Perform log analysis, troubleshooting, and root-cause analysis for production issues.
- Implement observability solutions for applications, cloud infrastructure, and services.
- Automate monitoring and operational activities using scripting.
- Support incident, problem, and change management processes.
- Collaborate with development, DevOps, and SRE teams to improve system reliability.
- Maintain monitoring standards, documentation, and operational procedures.
Primary Skills
- Microsoft Azure
- Splunk
- Grafana
- AppDynamics
- Cloud Monitoring & Observability
- Application Performance Monitoring (APM)
- Log Analysis & Troubleshooting
Secondary Skills
- Azure Monitor / Log Analytics
- Azure VMs, Storage, Networking
- Linux
- Python / PowerShell / Shell Scripting
- CI/CD
- Git
- ITIL / ServiceNow
Job Description
We are looking for an Azure Cloud & Observability Engineer with strong experience in Azure infrastructure and enterprise monitoring tools such as Splunk, Grafana, and AppDynamics.
Responsibilities
- Design, deploy, and manage Azure cloud infrastructure and services.
- Monitor application and infrastructure performance using Splunk, Grafana, and AppDynamics.
- Configure dashboards, alerts, health rules, and monitoring metrics.
- Perform log analysis, troubleshooting, and root-cause analysis for production issues.
- Implement observability solutions for applications, cloud infrastructure, and services.
- Automate monitoring and operational activities using scripting.
- Support incident, problem, and change management processes.
- Collaborate with development, DevOps, and SRE teams to improve system reliability.
- Maintain monitoring standards, documentation, and operational procedures.
Primary Skills
- Microsoft Azure
- Splunk
- Grafana
- AppDynamics
- Cloud Monitoring & Observability
- Application Performance Monitoring (APM)
- Log Analysis & Troubleshooting
Secondary Skills
- Azure Monitor / Log Analytics
- Azure VMs, Storage, Networking
- Linux
- Python / PowerShell / Shell Scripting
- CI/CD
- Git
- ITIL / ServiceNow
Job Summary
We are looking for an experienced Observability Engineer with strong expertise in ThousandEyes, Splunk, database technologies, and Python automation. The candidate will be responsible for monitoring application, network, and infrastructure performance, identifying issues, and developing automation solutions to improve system visibility, reliability, and operational efficiency.
Required Skills
- Observability
- ThousandEyes / Cisco ThousandEyes
- Splunk
- OracleDB
- MongoDB
- SQL
- Python Automation
Roles & Responsibilities
- Implement and support observability and monitoring solutions across applications, networks, and infrastructure.
- Work with ThousandEyes for network and digital experience monitoring.
- Configure and maintain monitoring dashboards, alerts, and performance metrics.
- Use Splunk for log analysis, monitoring, troubleshooting, and reporting.
- Work with OracleDB, MongoDB, and SQL for data analysis and troubleshooting.
- Develop Python scripts for monitoring and operational automation.
- Analyze performance issues and identify root causes across applications and infrastructure.
- Collaborate with application, infrastructure, and network teams to resolve incidents.
- Improve monitoring, alerting, and automation processes.
- Prepare performance and monitoring reports and provide actionable insights.
Mandatory Skills
- 7+ years of relevant experience
- Strong experience in Observability / Monitoring
- Hands-on experience with ThousandEyes
- Splunk
- Python Automation
- SQL
- OracleDB / MongoDB
Job Summary
We are looking for a Senior Observability Engineer with strong expertise in ThousandEyes, Splunk, and Monitoring & Observability Engineering. The candidate should have experience implementing and enhancing monitoring solutions, along with basic Python automation scripting.
Primary Skills
- ThousandEyes
- Splunk
- Monitoring & Observability Engineering
- Oracle Database
- SQL
- MongoDB
- Python Automation
Key Responsibilities
- Implement, configure, and enhance enterprise monitoring and observability solutions.
- Work extensively with ThousandEyes for network and application performance monitoring.
- Develop and maintain monitoring dashboards, alerts, and reports using Splunk.
- Monitor application, infrastructure, network, and database performance.
- Work with Oracle Database, SQL, and MongoDB for monitoring and troubleshooting.
- Develop basic Python automation scripts to improve monitoring and operational efficiency.
- Analyze performance issues and support troubleshooting and root cause analysis.
- Collaborate with application, infrastructure, network, and database teams to resolve observability-related issues.
- Continuously improve monitoring coverage, alerting, and operational processes.
Secondary Skills
- GenAI Concepts
- SaaS Architecture Concepts
- Cloud Application Architecture
Ideal Candidate Profile
- 7+ years of experience in Observability / Monitoring Engineering.
- Strong hands-on experience with ThousandEyes and Splunk.
- Good understanding of databases including Oracle, SQL, and MongoDB.
- Basic hands-on experience with Python automation.
- Understanding of application, infrastructure, and network monitoring.
- Exposure to GenAI, SaaS, or Cloud Application Architecture is an added advantage.
Very strong infra engineer to administer Linux based VMs (and few Windows VMs as well).
Must have strong knowledge and hands-on on docker, Kubernetes
Must be good at monitoring (AppDynamics, Prometheus, Grafana) and logging (Splunk)
Develop automation scripts using Shell and Python. Must have good knowledge in Ansible.
Should be good at optimize/finetune server configurations.
Should be good in troubleshoot issues and fix them.
Position Overview
The AI Observability Engineer will be instrumental in implementation of scalable, cloud-native solutions to meet the growing needs of our Data & Development team. The successful candidate will demonstrate the ability to abstract complexity and create reusable, scalable patterns that accelerate development. The AI Observability Engineer will build and maintain a robust framework to ensure the reliability and maintainability of DPR Construction's complex AI systems.
Responsibilities
- Standardize observability practices across AI/ML and other development teams including logging, metrics, tracing, and model performance monitoring, ingesting data from multiple platforms
- Lead hands-on implementation of automation-first DevOps and MLOps practices, enabling infrastructure-as-code and consistent, repeatable environment provisioning
- Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly detection
- Deploy, maintain and monitor containerized ML workloads
- Extend existing CI/CD pipelines to support automated infrastructure changes and ML workflows
- Implement AI-driven data validation, schema and concept drift detection and metadata management.
- Establish governance frameworks for AI systems, including bias detection, explainability, and auditability
- Extend existing Azure RBAC strategy by automating role and permission management to reduce manual intervention
- Develop automated test suites for model performance, regression, edge cases and bias validation
- Monitor model KPIs (accuracy, precision, recall, latency, calibration)
- Ensure reproducability of experiments and production models
- Act as a technical point of contact for DevOps and MLOps practices, developing reusable patterns, documentation, and proof-of-concepts to drive adoption
Qualifications
- Bachelor’s degree in computer science, Data Science, Information Systems, or a related field
- 5+ years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering
- Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure
- Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn
Hiring Platform Engineer
Exp: 6 -- 10 yrs
Edu : BE/B.tech/MCA
Work Location : Pune
Skills :
Platform monitoring ,Incident trouble shooting, Incident recovery, openshift ,kubernetes.
2 years of IT operations, infrastructure, cloud or application support experience.
Exp in Linux command-line knowledge.
Exp in networking knowledge including IP addressing, DNS, ports and connectivity troubleshooting.
L2 Production Support, Event Management / Mission Control, Incident Management, Linux, Linux, observability, and batch monitoring
Mandatory Skills: L2 Production Support, Event Management / Mission Control, Incident Management, Linux, Linux, observability, and batch monitoring
Primary Skills:
- L2 Production Support, Event Management / Mission Control, ServiceNow, Production Monitoring, Splunk / AppDynamics / ThousandEyes









