Join our dynamic Engineering, AI & Data team as a Senior Consultant specializing in Site Reliability Engineering (SRE). This role is instrumental in empowering and driving mission-critical solutions, whether modernizing existing systems or implementing cutting-edge technology products and platforms. You will contribute to enhancing financial performance, accelerating digital business initiatives, and fueling growth through innovation.

This is an exciting opportunity to work with a leading entity in the engineering domain, contributing to robust and scalable solutions.

Engage in Site Reliability Engineering practices on AWS and GCP platforms.

Develop and implement solutions leveraging programming and scripting languages such as Shell, Python, and Java.

Deepen understanding of operating systems from an SRE perspective, including Linux and Windows kernel internals, process, and memory management.

Contribute to system design and architecture, focusing on distributed systems, microservices, high availability, load balancing, and disaster recovery.

Work with cloud infrastructure across AWS, GCP, and Azure.

Implement and manage monitoring and observability tools for metrics, logging, and tracing.

Drive automation initiatives for operations, deployments, monitoring, and scaling.

Utilize containerization and orchestration technologies like Docker and Kubernetes.

Apply reliability engineering principles, including SLAs, SLOs, SLIs, error budgets, and capacity planning.

Focus on performance optimization and security aspects within SRE practices.

Participate actively in incident management processes.

A Bachelor's degree in Engineering is required.

Proven experience in Site Reliability Engineering on AWS/GCP is essential.

Proficiency in programming and scripting, including Shell scripting, Python, Java, and API development, along with strong debugging skills.

Solid understanding of operating systems from an SRE viewpoint, covering Linux, Windows, kernel internals, process, and memory management.

Experience with system design and architecture, specifically in distributed systems, microservices, high availability, load balancing, and disaster recovery.

Familiarity with cloud infrastructure such as AWS, GCP, and Azure.

Expertise in monitoring and observability tools (metrics, logging, tracing).

Demonstrated ability in automation for operational tasks, deployments, monitoring, and scaling.

Experience with containerization and orchestration technologies (Docker, Kubernetes).

Knowledge of reliability engineering concepts including SLA, SLOs, SLIs, error budgets, and capacity planning.

Skills in performance optimization and understanding of security aspects are crucial.

Familiarity with incident management processes is expected.