Senior Data Dog Engineer

Hiring: DevOps Lead

📍 Kochi / Trivandrum / Remote

💼 Full-time

🕐 General Shift | Australian Overlap

We are looking for an experienced DevOps Lead to join our team.

🔹 Key Responsibilities

Implement and continually improve the observability platform using Datadog, particularly from a user experience perspective.

Work across engineering squads as a virtual team member, supporting their DevOps, infrastructure, and observability requirements.

Configure and manage Datadog RUM, Session Replay, Distributed Tracing, and APM.

Support campaign readiness activities, including load and performance testing.

Participate in gamedays and incident response activities for production systems.

Liaise closely with the managed infrastructure provider on infrastructure requirements and activities.

🔹 Essential Skills & Requirements

✅ 7+ years of relevant DevOps / Cloud / Observability experience

✅ Strong hands-on experience with Datadog

✅ Strong experience with RUM, Session Replay, Distributed Tracing, and APM

✅ Solid experience with AWS

✅ Strong Infrastructure-as-Code experience using CloudFormation and AWS CDK

✅ Good working knowledge of GitHub Actions and AWS CodePipeline

✅ Real incident response experience on high-traffic systems

✅ Experience with Load & Performance Testing

✅ Strong problem-solving and communication skills

✅ Ability to work closely with infrastructure partners and internal platform teams

🔹 Skills - Good to Have

⭐ Experience with high-traffic platforms

⭐ Experience with campaign readiness and gamedays

⭐ Infrastructure partner management

⭐ Advanced AWS observability

⭐ Performance engineering

📌 Experience: 7+ Years

📌 Work Location: Kochi / Trivandrum / Remote

📌 Shift: General Shift with Australian Overlap

📌 Remote: Mandatory 1 week at office

📩 Interested candidates can share their resume

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

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

Job Summary:

We are looking for a Senior SRE/DevOps Engineer with strong experience in site reliability, automation, monitoring, observability, and production support. The candidate will be responsible for ensuring the reliability, availability, security, and performance of enterprise platforms.

Key Responsibilities:

• Own reliability, availability, security, and performance of enterprise browser platforms.
• Manage access and identity controls, Group Policy, and SAML/SSO integrations.
• Handle CI/CD deployments, configuration management, monitoring, and health checks.
• Develop automation and operational workflows using Python and Bash.
• Perform performance monitoring and production troubleshooting.
• Implement and maintain observability frameworks.
• Work with monitoring tools such as Datadog, Splunk, Dynatrace, Prometheus, and Grafana.
• Participate in incident management, RCA, and continuous improvement activities.
• Support highly available production environments in a 24/7 shift model.
• Collaborate with application, infrastructure, security, and operations teams.

Mandatory Skills:

• 10+ years of experience in SRE / DevOps.
• Strong hands-on experience in Python and Bash scripting.
• Experience with CI/CD and configuration management.
• Strong knowledge of monitoring and observability.
• Hands-on experience with Datadog, Splunk, Dynatrace, Prometheus, or Grafana.
• Experience with SAML/SSO, Identity & Access Management, and Group Policy.
• Banking domain experience.

🚀 Hiring: Senior Azure Platform Engineer | Azure | Terraform | Kubernetes

📍 Location: India

💼 Employment: Full-Time | Long-Term

🎯 Experience: 10+ Years | 8+ Years Hands-on Azure

🔑 What We’re Looking For

▪️ Strong expertise in Azure Cloud Platform & Landing Zone Architecture

▪️ Advanced hands-on experience with Terraform & reusable IaC modules

▪️ Expertise in Kubernetes, Helm & container platforms

▪️ Strong understanding of Azure Networking, Entra ID, RBAC & Azure Policy

▪️ Experience with GitHub, GitHub Actions / Azure Pipelines & CI/CD

▪️ Hands-on GitOps & ArgoCD experience

▪️ Strong observability skills with Prometheus, Grafana & Azure Monitor

▪️ Experience designing and supporting microservices architectures

▪️ Knowledge of security, policy-as-code and IaC security scanning

▪️ Exposure to Azure Arc / Azure Local / Azure Stack HCI is a plus

What You Will Own 

Platform Architecture 

• Full architectural ownership of the non-AWS toolchain: CI/CD, observability, event streaming, automation, secrets, and deployment infrastructure 
• Define, build, and enforce platform standards across portfolio products 
• Terraform IaC for all infrastructure — nothing provisioned manually, everything versioned and reviewed 
• Self-service developer platform so product teams ship without waiting on platform 

Event Streaming & Pipeline Infrastructure 

• Own the event streaming architecture, operational standards, and health monitoring across all products using real-time pipelines 
• Design and maintain batch processing infrastructure alongside live event flows 
• Ensure pipeline reliability, throughput, and cost are actively managed at scale 

CI/CD & Deployment 

• Build and maintain CI/CD pipelines (GitHub Actions) across all portfolio products 
• Automate triage and retry logic for known failure classes — flaky tests, dependency timeouts, OOM kills — so engineers are only paged for genuinely novel failures 
• Deployment standards: release management, rollback mechanisms, canary and blue-green patterns where justified 

Observability & Reliability 

• Own the full observability stack: Grafana, Prometheus, and Loki across all products 
• SLOs and error budgets defined per product; reliability tracked consistently 
• Build alerting that correlates signals and surfaces diagnostic context alongside notifications — so on-call engineers arrive at an incident with hypotheses, not a blank screen 
• Incident response: on-call design, escalation playbooks, post-mortem facilitation 
• Automated remediation scoped to a defined set of safe, idempotent actions — container restarts, ECS task scaling, known rollback patterns. Novel or ambiguous failures escalate to a human with full context attached 

Acquisition Onboarding 

• Platform audit and gap analysis for every new acquisition — assessing CI/CD maturity, IaC coverage, observability gaps, and security posture 
• Migration plan and execution for each portfolio company joining the platform.
• Target: full platform integration within a defined window per acquisition 

What We're Looking For 

Experience & Background 

• 8–12 years in platform engineering, DevOps, or SRE — with clear evidence of increasing ownership over time 
• Strong Terraform depth across multi-environment, multi-account setups 
• CI/CD ownership across a multi-product environment with GitHub Actions 
• Experience with event streaming infrastructure at production scale — design, operations, reliability, and cost management 
• Hands-on Grafana, Prometheus, and Loki in production 
• AWS operational depth: ECS, EKS, RDS, IAM, VPC, CloudWatch, Cost Explorer 
• SRE fundamentals: SLOs, error budgets, on-call design, post-mortem culture 
• Acquisition or greenfield platform integration experience strongly preferred 

Cloud Expertise(Azure):

• Strong understanding of cloud services and resources like AI services, webapp, database, including monitoring tools like Azure Monitor and Log Analytics.

• Experience with Infrastructure as Code (IaC) tools such as Arm template / Bicep/Terraform.

• Deep understanding of Networking concepts(DNS, DHCP , Hub and Spoke).

• Understanding on policies and security aspects of cloud.

Kubernetes & Helm:

• In-depth knowledge of Kubernetes concepts such as pods, services, ingress, config maps, and secrets.

• Understand of Kubernetes templates and its deployment.

• Proficiency with Helm/ Kustomize or equivalent for Kubernetes package management and deployment automation.

• Implement Kubernetes best practices, including security, networking, and scaling.

• Concepts of Docker and Containers

CI/CD & Programming:

• Hands-on experience with YAML-based CI/CD pipelines (e.g., Azure DevOps, GitHub Actions).

• Familiarity with scripting and automation tools such as PowerShell, Azure CLI, or Bash.

• Proven skill in python programming and concepts.

Monitoring and Observability:

Expertise in creating and managing Grafana dashboards for visualizing metrics and logs.

• Knowledge of Log Analytics & Azure Application Insights for performance monitoring and tracing.

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 

Azure DevOps Engineer

Experience

5-10 years of hands-on experience in Platform Engineering, Cloud Engineering, SRE, DevOps or Infrastructure Engineering roles.

Priority 1 – Must Have (Hands-On)

Azure Cloud Platform

·        Strong hands-on experience supporting Azure workloads in production environments.

·        Experience designing, building and supporting Azure infrastructure using Terraform.

·        Good understanding of Azure networking and connectivity patterns.

·        Experience supporting:

Ø AKS

Ø Application Gateway

Ø Azure Traffic Manager

Ø Key Vault

Ø Azure Monitor / Log Analytics

Ø Managed Identities

Ø Service Principals

Ø Private Endpoints

Ø VNets, NSGs and Route Tables

Kubernetes / AKS

• Strong practical experience operating and supporting AKS.
• Ability to troubleshoot:

Ø Pod failures

Ø Ingress issues

Ø DNS issues

Ø SSL/TLS certificate issues

Ø Network routing issues

Ø Performance and availability incidents

• Experience with:

Ø Helm

Ø Ingress Controllers

Ø Cluster upgrades

Ø Scaling

Ø Monitoring

Terraform

·        Strong hands-on experience writing and maintaining Terraform.

·        Experience creating reusable modules.

·        Experience managing:

·        State files

·        Remote backends

·        Environment promotion

·        Infrastructure lifecycle

Linux & Scripting

·        Strong Linux administration fundamentals.

·        Practical experience troubleshooting production issues.

·        Bash scripting mandatory.

·        Python desirable.

Application Support / Troubleshooting

Must be comfortable supporting business applications end-to-end.

 Priority 2 – Highly Desirable

GitHub & DevOps Platform

Hands-on experience with:

·        GitHub Enterprise

·        GitHub Actions

·        Shared workflows

·        Reusable pipelines

·        Repository onboarding

·        Branch protections

·        GitHub security features

Experience supporting:

·        Runner issues

·        Disk space issues

·        Network connectivity issues

·        Dependency failures

·        Self-hosted runners lifecycle management

API Management

Pipeline failures

GitOps

Experience with:

·        ArgoCD

·        GitOps deployment models

·        Kubernetes deployment automation

Monitoring & Observability

Experience working with:

·        Prometheus

·        Grafana

·        Azure Monitor

·        Log Analytics

·        Application Insights