Senior Data Dog Engineer

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 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.

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 

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 

- 6–7 years of experience operating and enhancing enterprise-scale data platforms.

- Hands-on experience applying DataOps, DevOps, and software engineering practices to data platform operations.

- Professional experience working with AWS cloud environments.

- Experience monitoring, troubleshooting, and remediating issues across data pipelines, orchestration tools, and platform services.

- Working knowledge of data observability concepts and practices.

- Hands-on proficiency with SQL, relational database concepts, and data warehousing.

Tasks & Responsibilities: (Major task and role person will have to perform – list all the relevant points)    

Together with the Business Cloud Services team, you will design, deploy, and operate a cloud‑native Kubernetes PaaS platform on Azure, ensuring high availability, security, and operational excellence.

Your main duties include:

·      Drive cloud‑native automation and self‑service capabilities, ensuring platform security, availability, and disaster recovery readiness

·      Design, operate, and continuously improve Kubernetes clusters and PaaS environments on Azure / AKS

·      Collaborate closely with development teams on deployment strategies, operational requirements, and platform integration

·      Review and maintain infrastructure‑as‑code configurations, CI/CD pipelines, and cloud‑native deployments

·      Build and maintain CI/CD pipelines using Azure DevOps

·      Implement and operate infrastructure‑as‑code solutions using Terraform, Helm, and Ansible

·      Manage containerized workloads and orchestration across cloud‑native environments

·      Set up, operate, and enhance monitoring, logging, and alerting stacks using tools such as Prometheus and Grafana

·      Coordinate with support teams on platform incidents, escalations, and post‑incident analysis

·      Contribute to incident response, continuous improvement, and operational stability

·      Support the development and refinement of DevOps practices, runbooks, and operational standards

·      Actively contributes to improving developer experience and platform reliability

Education & Trainings + Certifications: (Basic & Professional)

·      Bachelor’s degree (Preferably engineering graduate)

·      Azure Solutions Architect Expert Certification is a plus.

·      (optional) ITIL Foundation 

Technical know-how: (Mention the technology on which person must be experienced)

Mandatory

o  Bachelor’s degree in computer science, Information Systems, or a related field

o  5+ years of relevant professional experience in DevOps, Cloud Engineering, or Platform Engineering roles

o  Strong Linux system administration skills for operating production‑grade cloud‑native platforms

o  Proven experience with Microsoft Azure, including AKS and Azure DevOps tooling

o  Strong expertise in Kubernetes, including cluster operations, RBAC, networking, and storage

o  Hands‑on experience with container technologies such as Docker and container registries

o  Proficiency with Terraform, Helm, Ansible, and PowerShell

o  Experience building and operating CI/CD pipelines using Azure DevOps or equivalent tools

o  Cloud‑native monitoring and observability experience using Prometheus, Grafana, and alerting pipelines

o  Solid understanding of security and compliance requirements such as PCI DSS and SOC2

o  Scripting skills for automation and tooling (Bash, Python, PowerShell)

o  Practical experience using Git for version control

o  Excellent communication skills in English (Spanish is a plus)

o  Automation‑first mindset and strong collaboration skills within Agile teams

Good to know

Principles of Agile Software Development.

·      GitHub Actions, GitLab CI, Jenkins, Azure DevOps

·      Containers: Docker, Kubernetes (EKS / AKS / GKE)

·      Configuration Management: Ansible

About the company:

We empower US healthcare payers with a truly next-generation, cloud-native, holistic, and customizable platform designed to prevent and adapt to the ever-evolving inaccuracies in healthcare claims and payments. By reducing complexity and administrative costs, we offer a unified, healthcare-dedicated platform backed by top VCs like BeeNext, 3One4 Capital, and Saison Capital.

Position Overview:

We are looking for an experienced DevOps Engineer to join our team in Bengaluru. In this role, you will be responsible for building, optimizing, and maintaining scalable, secure, and highly available multi-cloud infrastructure that supports our engineering teams. The ideal candidate brings strong hands-on experience with Kubernetes, Infrastructure as Code (Terraform), and robust monitoring/observability stacks to enable seamless, reliable, and automated deployments.

Key Responsibilities:

• Container Orchestration: Deploy, scale, and manage containerized workloads on Kubernetes (EKS, AKS, and GKE).
• Infrastructure as Code (IaC): Build and maintain modular, reusable, and version-controlled infrastructure using Terraform across AWS, Azure, and GCP.
• Monitoring & Observability: Set up, manage, and optimize monitoring, logging, and alerting stacks (e.g., Prometheus, Grafana, ELK/EFK, Loki, Datadog).
• CI/CD Pipeline Management: Own, improve, and automate CI/CD pipelines to enable fast, reliable, and frictionless software releases.
• System Reliability & SRE Practices: Implement best practices for system reliability, including defining SLIs/SLOs, managing incident response, and participating in on-call support.
• Troubleshooting & Support: Diagnose and resolve complex production issues across infrastructure, networking, and application layers.
• Security & Compliance: Implement infrastructure security best practices, including IAM policies, secrets management, and network security.
• Automation: Eliminate repetitive operational tasks by writing clean, efficient scripts in Python, Bash, or Go.
• Operations & Planning: Participate in capacity planning, cost optimization, disaster recovery, and infrastructure scaling initiatives while maintaining clear documentation and runbooks.

Requirements :

• Solid working experience with cloud providers, specifically AWS, Azure, or GCP.
• Strong understanding of containerization (Docker) and container orchestration concepts.
• Familiarity with Linux system administration and networking fundamentals.
• Experience with version control systems (Git) and GitOps workflows (ArgoCD/Flux is a plus).
• Strong problem-solving skills and the ability to thrive in a fast-paced, collaborative environment.

Qualifications :

Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related technical field (or equivalent practical experience)

Key Skills:

• The ideal candidate must possess deep expertise in container orchestration, specifically hands-on experience managing Kubernetes ecosystems—including Helm charts, cluster networking, and RBAC policies—alongside a foundational mastery of Docker containerization.
• Proficiency in managing cloud architecture as software is essential, with a heavy emphasis on Terraform execution, including advanced module creation, state management, and multi-environment workspaces.
• A strong capability to implement full-stack visibility is required, utilizing tools like Prometheus, the Grafana LGMT stack, ELK/EFK, or Loki to build highly optimized monitoring, alerting, and logging systems.
• Candidates should have a proven track record of constructing and scaling automated deployment pipelines using industry-standard platforms such as Jenkins, GitLab CI, GitHub Actions, or Azure DevOps to minimize release friction. .
• Strong core programming fundamentals are required to automate repetitive infrastructure tasks, with practical proficiency in Python, Bash, or Go.
• Familiarity with cutting-edge cloud-native technologies is highly desirable, including enterprise service meshes (Istio, Linkerd), comprehensive cloud security frameworks (HashiCorp Vault, OPA, Trivy), and a data-driven approach to cloud cost management and FinOps practices.

Work Location: Jayanagar - Bangalore.

Work Mode: Work from Office, hybrid- 3 days WFO

Note: We are looking for immediate joiners & Bangalore Candidates only

Benefits:

• Best-in-class compensation
• Health insurance for Family
• Personal Accident Insurance
• Friendly and Flexible Leave Policy
• Certification and Course Reimbursement
• Medical Coding CEUs and Membership Renewals
• Health checkup
• And many more!

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.