Description

Key Skills: DevOps, Jenkins, Kubernetes, SDLC, Linux, Git, Kafka, Elasticsearch, Helm, Grafana

Good to Have Skills: Experience with monitoring and observability tools like Dynatrace, Splunk, DataDog. Knowledge of deployment architecture and cloud best practices. Experience with managing EOL components and driving process improvements. Proficiency in infrastructure security. Demonstrated experience using enterprise-authorized AI capabilities within the work environment. Certifications in cloud platforms (AWS, Azure, Google Cloud). Experience in financial services or related industry. Strong communication and collaboration skills.

Roles & Responsibilities:

• Apply technical knowledge and problem-solving methodologies to projects of moderate scope with focus on improving data and systems running at scale.
• Ensure end to end monitoring of applications and resolve most nuances while determining appropriate escalation path.
• Execute conventional approaches to build or break down technical problems and drive daily activities supporting standard capacity process applications.
• Partner with application and infrastructure teams to identify potential capacity risks and govern remediation statuses.
• Consider upstream and downstream data and systems or technical implications for comprehensive solution design.
• Be accountable for making significant decisions for projects consisting of multiple technologies and applications.
• Use enterprise-authorized AI capabilities within work environment to accelerate monitoring and capacity analysis and documentation.
• Apply reuse-first and AI-assisted approaches to identify recurring capacity risks and improve remediation workflows.

Experience Required: Formal training or certification on infrastructure engineering concepts and 3+ years applied experience. Hands-on experience in DevOps with strong focus on Jenkins, Kubernetes, and SDLC pipelines. Proven experience in deployment architecture and cloud best practices

Key Skills

Education

Any Graduate