Kubernetes:
Strong working experience in core concepts (autoscaling, RBAC, pod placement) and advanced areas such as Karpenter and service mesh.
AWS Cloud:
Hands-on experience with
CloudWatch, EKS, ECS, DynamoDB
, and cloud infrastructure provisioning.
Infrastructure as Code (IaC):
Expertise in
Terraform
and
Terragrunt
, with ability to create and manage reusable modules.
Scripting:
Proficiency in
Shell, PowerShell, or Python
for automation tasks.
CI/CD:
Strong understanding and experience in
pipeline creation, deployment automation
, and integration using tools such as
Jenkins, Bamboo, Harness
, or
Azure DevOps
.
Containerization:
Skilled in
Docker
and
Kubernetes
setup, management, and troubleshooting.
DevOps Tools Integration:
Experience with
Sonarqube
,
Nexus/Artifactory
,
Maven/Ant
,
Git/Bitbucket
, and
ELK/Splunk
.

Good to Have Skills:

Experience with
Harness platform
(pipelines, deployments, configuration, and security).
Knowledge of
Azure
or
GCP
DevOps tools and cloud environments.
Experience in
application migration
from on-premises to cloud.
Familiarity with
SecDevOps
and tools such as
Blackduck, Veracode, Checkmarx
.
Exposure to
Agile methodologies
and
Jira
project setup and management.
Knowledge of
C#/.NET
debugging,
ARM templates
, and
Desired State Configuration (DSC)
.
Understanding of
software security compliance
(GDPR/OWASP).

Act under the guidance of DevOps leadership,
leading multiple Agile teams
.
Design, install, and troubleshoot CI/CD pipelines
and software using modern DevOps tools.
Automate infrastructure provisioning
on cloud and on-premises environments.
Develop and maintain
automation scripts and playbooks
for deployment, configuration, and infrastructure setup.
Create and configure
tools and automation frameworks
for integration within the overall DevOps architecture.
Guide and mentor
DevOps Engineers
on technical and operational aspects.
Optimize
efficiency, cost, and quality
of DevOps processes and toolchains.
Ensure
security and compliance
are integrated throughout the CI/CD lifecycle.
Measure and improve
process efficiency
using metrics such as deployment frequency, change lead time, failed deployments, and MTTR.
Support and improve
monitoring, observability, and incident management
practices.

Measures of Outcomes:

Quality and reliability of deliverables
On-time delivery and adherence to specifications
Error rate and completion rate across SDLC stages
Number of reusable components developed
SLA/KPI adherence for onboarding projects
Stakeholder satisfaction and effective collaboratio

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