Description

Job Description

 Technical Competencies

Candidates are not expected to be experts in every tool, but should bring strong handson experience across several of the following areas:

AWS Services: Hands-on experience with AWS compute and migration patterns, including ECS, EKS, Lambda, CloudWatch, and related cloud services.

Cloud Migration: Practical understanding of on-prem to cloud migration strategies, workload assessment, testing, cutover, and post-migration validation.

Programming and Automation: Experience with Python, Java, Shell, or similar languages to build scripts, utilities, and automation frameworks.

APIs and Integration: Working knowledge of RESTful APIs, API design, and API Gateway patterns.

CI/CD and Version Control: Strong experience with GitLab, Jenkins, Maven, or similar tools supporting automated build, test, and deployment pipelines.

Batch Scheduling: Experience with batch scheduling platforms such as Autosys, Control-M, Cron, or equivalent workflow orchestration tools.

Observability: Familiarity with monitoring, logging, alerting, and troubleshooting using tools such as CloudWatch, Splunk, or equivalent platforms.

Automation Excellence: Ability to design repeatable automation and apply AI-assisted engineering approaches to improve migration scale, quality, and efficiency.

Core Competencies:

Exceptional analytical, troubleshooting, and debugging skills.

Strong ownership mindset with the ability to drive work to closure and meet commitments.

Clear written and verbal communication, including concise status updates, structured briefings, and proactive stakeholder management.

Effective collaboration across application, infrastructure, platform, and global engineering teams.

Ability to work constructively across time zones, build alignment, and resolve issues with urgency and professionalism.

Strong integrity, sound judgment, and commitment to good conduct and ethical decision making.

High energy, intellectual curiosity, and willingness to surface risks early, ask thoughtful questions, and continuously improve.

Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Applied Mathematics, or a related quantitative discipline.

Experience: 3–5 years of hands-on engineering experience in a collaborative, team-based environment.

Programming: Professional proficiency in Python, Java or a similar programming/scripting language.

Systems: Strong Unix/Linux fundamentals with the ability to troubleshoot application, deployment, environment, and runtime issues.

Methodology: Familiarity with SDLC practices, CI/CD delivery models, change management, and Kubernetes-based deployments

Key Skills

Education

Any Graduate